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ORCIDIJCNN 1999: Washington, DC, USA
- International Joint Conference Neural Networks, IJCNN 1999, Washington, DC, USA, July 10-16, 1999. IEEE 1999
Neural Memory, Learning and Adaptation
- David D. Vogel:
A partial model of cortical memory based on disinhibition. 1-5 - Javier Ropero Peláez, Marcelo Godoy Simões:
A computational model of synaptic metaplasticity. 6-11 - Simona Doboli, Ali A. Minai, Phillip J. Best:
Generating smooth context-dependent neural representations. 12-15 - A. N. Radchenko:
Biophysical basis of neural memory. 16-20 - Witali L. Dunin-Barkowski, Donald C. Wunsch:
Cerebellar learning: a possible phase switch in evolution. 21-26 - Rushi Bhatt, Karthik Balakrishnan, Vasant Konavar:
A hybrid model for rodent spatial learning and localization. 27-32 - K. F. Wilson, Charles F. Osborne:
A numerical exploration of a stochastic model of human list learning. 33-37 - Neill R. Taylor, John G. Taylor:
Learning to generate temporal sequences by models of frontal lobes. 38-41 - Roman Borisyuk, Frank Hoppensteadt:
Oscillatory model of the hippocampal memory. 42-45 - John G. Taylor:
A mathematical analysis of adaptive synapses. 46-51 - Robert Kozma, Walter J. Freeman:
A possible mechanism for intermittent oscillations in the KIII model of dynamic memories - the case study of olfaction. 52-57 - András Lörincz, György Buzsáki:
Computational model of the entorhinal-hippocampal region derived from a single principle. 58-63 - Peter Aszalos, Szabolcs Kéri, György Kovács, György Benedek, Zolton Janka, András Lörincz:
Generative network explains category formation in Alzheimer patients. 64-68
Global Brain Models
- Simon Y. Berkovich:
Probing the architecture of the brain in experimentation with afterimages. 69-73 - Asim Roy:
Brain's internal mechanisms - a new paradigm. 74-79 - Thomas E. Portegys:
A connectionist model of motivation. 80-85 - Frank R. Funderburk, Karen I. Bolla:
Steps toward development of an integrated neurobiological model of cocaine misuse effects. 86-90 - John G. Taylor:
Neural networks for consciousness: the central representation. 91-96 - Shannon R. Campbell:
Rate of synchrony in locally coupled chains of relaxation oscillators. 97-102 - Robert Homer:
A neural network model of personality. 103-108 - Iren Valova, Yukio Kosugi:
Modeling higher level processing functions inherent to the human brain. 109-112 - Steven L. Bressler, Mingzhou Ding:
Coordination dynamics in large-scale cortical networks. 113-116 - Carlos Alberto Rossi, Ladislao Bodnar:
Artificial learning. 117-120 - Svetlana Levitan, Ioana Stoica, James A. Reggia:
A model of lateralization and asymmetries in cortical maps. 121-124
Vision
- Javier Ropero Peláez, Marcelo Godoy Simões:
Pattern completion through thalamo-cortical interaction. 125-130 - Karen G. Haines, John A. Moya, Thomas P. Caudell:
Modeling nonsynaptic communication between neurons in the lamina ganglionaris of Musca domestica. 131-136 - Guy D. Chun, Thomas P. Caudell:
A model of saccadic generation based on the neurobiology of the superior colliculus. 137-141 - Thaddeus A. Roppel, Denise M. Wilson, Kevin Dunman, Vlatko Becanovic, Mary Lou Padgett:
Design of a low-power, portable sensor system using embedded neural networks and hardware preprocessing. 142-145 - Jeremy B. Badler, Edward L. Keller:
Decoding of information from distributed motor maps. 146-151 - Alexander G. Sukhov, Tattiana G. Bezdudnaya:
Peculiarities of frequency-phase filtering of signals at different stages of information processing in rat barrel cortex. 152-155 - Dmitry Shaposhnikov, Lubov N. Podladchikova:
Local nonuniformity of the visual perception in the peripheral vision field. 156-159 - Kô Sakai, S. Tanaka:
Analysis of spatial nonlinear responses in cortical complex cells. 160-163 - Yu Bo, Liming Zhang:
Knowledge matching model with dynamic weights based on the primary visual cortex. 164-169 - Shigeki Nakauchi, Shiro Usui, Jussi Parkkinen, Pertti Silfsten:
Computational explanations for color transparency. 170-173 - Vitali V. Gavrik:
Single-pigment optical mechanism for color opponency in a photoreceptor cell. 174-177 - Yoshifusa Ito, Tohru Yagi, H. Kanda, S. Tanaka, M. Watanabe, Yoshiki Uchikawa:
Cultures of neurons on micro-electrode array and control of their axon growth in hybrid retinal implant. 178-181 - Pamela Abshire, Andreas G. Andreou:
Relating information capacity to a biophysical model for blowfly retina. 182-187 - Chota M. Markan, Basabi Bhaumik:
Diffusive Hebbian model for orientation map formation. 188-191 - Michael Becker, Rolf Eckmiller, Ralph Hünermann:
Psychophysical test of a tunable retina encoder for retina implants. 192-195 - Takehiko Ogawa, Takashi Minohara, Hajime Kanada, Yukio Kosugi:
Realization of geometric illusions using artificial visual model based on acute-angled expansion among crossing lines. 196-199 - Hiroshi Kume, Yuko Osana, Masafumi Hagiwara:
Solving the binding problem with feature integration theory. 200-205
Modeling of the Hippocampal Function (Special Session)
- Nestor A. Schmajuk:
The hippocampus and the brain: a neural network model. 206-209
Sensor/Motor and Neural Processes
- Mark Glezer, Yuri Shkuro, James A. Reggia:
Simulated callosal lesions in a neural model of left and right hemispheric regions. 210-214 - Natalia Shevtsova, James A. Reggia:
Lesion effects in a bihemispheric letter-identification model. 215-218 - Witali L. Dunin-Barkowski, Sergey N. Markin, Lubov N. Podladchikova, Donald C. Wunsch:
Climbing fibre Purkinje cell twins are found. 219-222 - Hiroshi Wakuya, Katsunori Shida:
Acquired sensorimotor coordinated signal transformation in a bi-directional neural network model. 223-228 - Yong Li, Ning Lan, Fusheng Yang:
The inverse identification of neuromuscular system by using neural networks in elbow function self-correcting system. 229-232 - Kazutaka Someya, Atsushi Fujita, Yoshifumi Sekine, Kawyuki Aihara:
Chaotic phenomena of an active axon. 233-238 - I. E. Kanounikov, E. V. Antonova:
Comparison of fractal characteristics of the electroencephalogram at schoolchildren 10-12 years old in norm and with difficulties in learning. 239-242 - I. E. Kanounikov, E. V. Antonova, B. V. Kiselev, D. R. Belov:
Dependence of one of the fractal characteristics (Hurst exponent) of the human electroencephalogram on the cortical area and type of activity. 243-246 - Nicolas P. Rougier, Frédéric Alexandre:
Spatial knowledge transfer between models of hippocampus and associative cortex. 247-251 - Hervé Frezza-Buet, Frédéric Alexandre:
Modeling prefrontal functions for robot navigation. 252-257 - Shenchu Xu, Zhenxiang Chen, Jinshui Zhong, Boxi Wu, Guoqiang Gao, Hang Xiao, Jianping Wu, Yun Shi, Jian Chen, Xiaofan Yang:
The animal tests of chaotic signal therapy for epilepsy (CSTE). 258-261 - Zhenya He, Yifeng Zhang, Luxi Yang, Yuhui Shi:
Control chaos in nonautonomous cellular neural networks using impulsive control methods. 262-267 - Anthony N. Burkitt
, Graeme M. Clark:
Synchronization of the neural response to noisy periodic synaptic input. 268-273
Auditory System and Language
- Guy J. Brown, DeLiang Wang:
The separation of speech from interfering sounds: an oscillatory correlation approach. 274-279 - Xugang Lu, Daowen Chen:
Integrating spatial and temporal mechanisms in auditory neural fiber's computational model. 280-283 - Bing Xiang, Xihong Wu, Zhimin Liu, Huisheng Chi:
Auditory model based speech feature extraction and its application to speaker identification. 284-287 - Michiro Negishi, Daniel Bullock, Michael Cohen:
A self-organizing two-stream model of language comprehension. 288-292 - Ryuta Fukuda, Junko Hara, William Rodman Shankle, Toshio Inui, Masaru Tomita:
Predicting human cortical connectivity for language areas using the Conel database. 293-295 - Susan L. Denham, Michael J. Denham:
Synaptic depression may explain many of the temporal response properties observed in primary auditory cortex: a computational investigation. 296-300 - Gang Wang, Miki Haseyama, Nobuo Suga:
A recurrent network model for range processing of the mustached bat. 301-304 - Anthony N. Burkitt:
Analysis of neural response for excitation-inhibition balanced networks with reversal potentials for large numbers of inputs. 305-308
The Electronic Nose (Special Session)
- Paul E. Keller:
Overview of electronic nose algorithms. 309-312 - Dumitru Dumitrescu, Beatrice Lazzerini, Francesco Marcelloni:
Olfactory signal classification based on evolutionary computation. 313-316 - Geza Szekely, Mary Lou Padgett, Gerry V. Dozier, Thaddeus A. Roppel:
Odor detection using pulse coupled neural networks. 317-321
Higher Order and Recurrent Networks
- Tertulien Ndjountche, Rolf Unbehauen, Fa-Long Luo:
Signal separation processor based on second-order statistic algorithms. 322-327 - Shuxiang Xu, Ming Zhang:
Adaptive higher-order feedforward neural networks. 328-332 - Ming Zhang, Shuxiang Xu, Bo Lu:
Neuron-adaptive higher order neural network group models. 333-336 - Satoshi Matsuda:
"Optimal" neural representation of higher order for quadratic combinatorial optimization. 337-340 - Olivier Moynot, Manuel Samuelides:
Dynamics of large random recurrent neural networks: oscillations of 2-population model. 341-344 - Habtom W. Ressom:
Modeling a compression plant using recurrent neural networks. 345-348 - Alexander G. Parlos, Omar T. Rais, Amir F. Atiya:
Multi-step-ahead prediction using dynamic recurrent neural networks. 349-352 - Yee Chin Wong, Malur K. Sundareshan:
A simplex optimization approach for recurrent neural network training and for learning time-dependent trajectory patterns. 353-358 - Devasis Bassu, James T. Lo, Justin Nave:
Training recurrent neural networks with noisy input measurements. 359-363 - James T. Lo, Devasis Bassu:
Mathematical justification of recurrent neural networks with long and short-term memories. 364-369
Functional Approximation and Prediction
- Shuxiang Xu, Ming Zhang:
Approximation to continuous functionals and operators using adaptive higher-order feedforward neural networks. 370-374 - Gerald H. L. Cheang, Andrew R. Barron:
Estimation with two hidden layer neural nets. 375-378 - E. D. Avedyan, G. V. Barkan, I. K. Levin:
Synthesis of multilayer neural networks architecture (for the case of cascaded NNs). 379-382 - Danil V. Prokhorov, Lee A. Feldkamp:
Application of SVM to Lyapunov function approximation. 383-387 - Wolfgang Eppler, Hans N. Beck:
Piecewise linear networks (PLN) for function approximation. 388-391 - Guy Ferland, Tet Hin Yeap:
Prediction of nonlinear dynamical system output with multilayer perceptron and radial basis function neural networks. 392-397 - Irwin W. Sandberg:
Time-delay polynomial networks and quality of approximation. 398-403 - Andrzej Lozowski, Rafal Komendarczyk, Jacek M. Zurada:
Hamiltonian vector field for the Lorenz invariant set. 404-408 - Thomas Hanselmann, Anthony Zaknich, Yianni Attikiouzel:
Learning functions and their derivatives using Taylor series and neural networks. 409-412 - Takamasa Koshizen, Yves Rosseel, Yoshihiro Tonegawa:
A new EM algorithm using Tikhonov regularization. 413-418 - E. Basson, Andries P. Engelbrecht:
Approximation of a function and its derivatives in feedforward neural networks. 419-421
Math Foundations I
- Evgeny E. Dudnikov:
Increase the number of stable equilibrium points in a Hopfield-type neural network. 422-426 - Hiroki Suyari, Ikuo Matsuba:
New approach to the storage capacity of neural networks using the minimum distance between input patterns. 427-431 - Xinchuan Zeng, Tony R. Martinez:
Extending the power and capacity of constraint satisfaction networks. 432-437 - Hugo de Garis, Norberto Eiji Nawa, Michael Hough, Michael Korkin:
Evolving an optimal de/convolution function for the neural net modules of ATR's artificial brain project. 438-443 - Masahiko Yoshioka, Masatoshi Shiino:
Pattern coding based on firing times in a network of spiking neurons. 444-449 - Ernst M. Kussul, Dmitri A. Rachkovskij, Donald C. Wunsch:
The random subspace coarse coding scheme for real-valued vectors. 450-455 - Howard E. Michel, Abdul Ahad S. Awwal:
Enhanced artificial neural networks using complex numbers. 456-461 - Dan Ventura:
Implementing competitive learning in a quantum system. 462-466 - Arturo Hernández Aguirre, Cris Koutsougeras, Bill P. Buckles:
On model selection in SLT and linear basis neural networks. 467-472 - Ana Maria Tomé:
The generalized eigen-decomposition approach to blind source problems. 473-476 - Kayvan Najarian, Guy Albert Dumont, Michael S. Davies:
A learning-theory-based training algorithm for variable-structure dynamic neural modeling. 477-482 - Kazunori Miyamoto, Hirohisa Aman, Torao Yanaru, Masahiro Nagamatsu:
Symbolized particles store type neuron model and its application. 483-487 - Adrian Silvescu:
Fourier neural networks. 488-491
Math Foundations II
- Michael J. Healy:
Colimits in memory: category theory and neural systems. 492-496 - Xiuwen Liu, DeLiang Wang:
A boundary-pair representation for perception modeling. 497-501 - Yan Zhang:
On logical semantics of hybrid symbolic-neural networks for commonsense reasoning. 502-505 - Toshiyuki Tanaka:
Exploration of mean-field approximation for feedforward networks. 506-509 - Arnulfo P. Azcarraga, Marlene Rose Lim:
2D order of self-organizing Kristal maps. 510-513 - Osamu Araki, Kapcyuki Aihara:
Dual coding in a network of spiking neurons: aperiodic spikes and stable firing rates. 514-518 - Sorin Draghici:
Some new results on the capabilities of integer weights neural networks in classification problems. 519-524 - Michikio Yamana, Masatoshi Shiino, Masahiko Yoshioka:
Oscillator neural network model with distributed native frequencies. 525-528 - Ján Jockusch, Helge J. Ritter:
An instantaneous topological mapping model for correlated stimuli. 529-534 - Neil M. Branston, Wael El-Deredy:
Parameter selection and state dominance in hidden Markov models of neuronal activity. 535-539 - Lei Xu:
Bayesian ying-yang supervised learning, modular models, and three layer nets. 540-545 - Lei Xu:
BYY data smoothing based learning on a small size of samples. 546-551 - Lei Xu:
Bayesian ying-yang theory for empirical learning, regularization and model selection: general formulation. 552-557 - Kazuyoshi Tsutsumi, Kazuo Nakajima:
Maximum/minimum detection by a module-based neural network with redundant architecture. 558-561 - John D. Carew, Amir Assadi, Hamid Edhbalnia:
A method for investigating the nonlinear dynamics of the human brain from analysis of functional MRI data. 562-567
Nonlinear Problems and Programming
- Satoshi Matsuda:
Theoretical analysis of quantized Hopfield network for integer programming. 568-571 - Eric Bax:
Validation of fusion through linear programming. 572-575 - Anton M. Sirota, Alexander A. Frolov, Dusan Húsek:
Nonlinear factorization in the hippocampal neural structure. 576-581 - Youshen Xia, Jun Wang:
Primal neural networks for solving convex quadratic programs. 582-587 - Jun Wang, Youshen Xia:
A dual neural network solving quadratic programming problems. 588-593 - Jaques Reifman, Earl E. Feldman:
Nonlinear programming with feedforward neural networks. 594-598 - David B. McCaughan, David A. Medler, Michael R. W. Dawson:
Internal representation in networks of nonmonotonic processing units. 599-604 - Gerhard X. Ritter, Thad W. Beaver:
Morphological perceptrons. 605-610 - Michael Ciraula, Irwin W. Sandberg:
Uniform approximation of discrete-time nonlinear systems. 611-616 - Richard Labib:
New single neuron structure for solving nonlinear problems. 617-620 - Ravi Kothari, Ming Dong, Dinesh K. Bhatia:
Neighborhood induced stochastic resonance. 621-624 - Shi Zhong, Vladimir Cherkassky:
Factors controlling generalization ability of MLP networks. 625-630 - Wlodzislaw Duch, Rafal Adamczak:
Neural networks in non-Euclidean metric spaces. 631-636 - A. H. Sung, H. J. Li:
Using neural networks as an aid for solving engineering problems. 637-642
Optimization
- Sergei M. Obraztsov, Alexander L. Shimkevich:
A zero order minimization algorithm using a neural network. 643-645 - Michel Winter, Gérard Favier:
An extended Hopfield model for combinatorial optimization. 646-649 - D. Randall Wilson, Dan Ventura, Brian Moncur, Tony R. Martinez:
The robustness of relaxation rates in constraint satisfaction networks. 650-654 - S. A. Belbas:
Neural networks in 2-D continuous time. 655-658 - Akira Hirabayashi, Hidemitsu Ogawa:
What can memorization learning do? 659-662 - Dmitry O. Gorodnichy:
The optimal value of self-connection. 663-668 - Wlodzislaw Duch, Rafal Adamczak, Krzysztof Grabczewski, Grzegorz Zal:
Optimization of logical rules derived by neural procedures. 669-674 - Katsuhiko Murakami, Tohru Nakagawa:
Solving a graph layout problem using strictly digital neural networks with virtual slack-neurons. 675-679 - Kenya Jin'no:
Hysteresis neural networks for a combinatorial optimization problem. 680-683 - Ivan Nunes da Silva, Mário Eduardo Bordon, André Nunes de Souza:
Design and analysis of neural networks for systems optimization. 684-689
Theory and Chaos
- Zhae Liang, Nizam Omar, Elbert E. N. Macau:
Locally coupled chaotic oscillator network for scene segmentation. 690-694 - Frank Pasemann:
Synchronized chaos in coupled neuromodules of different types. 695-698 - Raymond Pavloski, Majid Karimi:
Self-trapping in an attractor neural network with nearest neighbor synapses mimics full connectivity. 699-704 - Dhananjay S. Phatak:
Relationship between fault tolerance, generalization and the Vapnik-Chervonenkis (VC) dimension of feedforward ANNs. 705-709 - Yunfan Gong, Wei Ren, X. Z. Shi, Sanjue Hu:
Noise reduction of chaotic interspike intervals (ISI) of neurons. 710-712 - Masaya Ohta:
On the self-feedback controlled chaotic neural network and its application to N-Queen problem. 713-716 - Hiroyuki Torikai, Toshimichi Saito:
Integrate-and-fire model with periodic inputs. 717-720 - Hidehiro Nakano, Toshimichi Saito:
Autonomous integrate-and-fire model with vibration. 721-724 - Christian Storm, Walter J. Freeman:
A novel dynamical invariant measure addresses the stability of the chaotic KIII neural network. 725-729 - Algis Garliauskas:
Chaos in neural networks with bistable dendrite membrane current-voltage relation. 730-735 - Walter J. Freeman:
Stochastic chaos versus deterministic chaos: a case for analog versus digital embodiment of devices for pattern recognition. 736-741
Associative Memory
- Taira Nakajima, Hiroyuki Takizawa, Hiroaki Kobayashi, Tadao Nakamura:
A self-organizing network system forming memory from nonstationary probability distributions. 742-745 - Yuko Osana, Masafumi Hagiwara:
Knowledge processing system using chaotic associative memory. 746-751 - Yuko Osana, Masafumi Hagiwara:
Chaotic associative memory for sequential patterns. 752-757 - Jiongtao Huang, Masafumi Hagiwara:
A new bidirectional associative memory based on distributed representation. 758-763 - Jiongtao Huang, Masafumi Hagiwara:
A combined multi-Winner multidirectional associative memory. 764-769 - Paul Watta, Nobuhiko Ikeda, Metin Artiklar, Ambiga Subramanian, Mohamad H. Hassoun:
Comparison between theory and simulation for the two-level decoupled Hamming associative memory. 770-774 - Winfried A. Fellenz, John G. Taylor:
Enhancing the storage capacity of binary associative memories. 775-780 - Yutaka Kawabata, Yoshimasa Daido, Shimmi Hattori:
Capacity of second-ordered bidirectional associative memory in the presence of noise bits. 781-786 - Masahiro Iwasaki, Tomonori Hashiyama, Shigeru Okuma:
Determining field of visual attention in associative memories. 787-790 - Yasuo Kinouchi, Masahiro Mizutani, Shoji Inabayashi:
An architecture for an adaptive associative memory system based on autonomous reactions between images. 791-794 - Jorge A. Horas, Cristian P. Mankoc:
Behavior of interactive neural networks as associative memories. 795-797 - Yasuaki Kuroe, Kenshu Koashi, Naoki Hashimoto, Takehiro Mori:
A learning method for synthesizing associative memory in neural networks. 798-803
Other Architectures
- R. Sunderam:
Partitioned architectures for large scale data recovery. 804-807 - Shoujue Wang, Huaxiang Li, Xiangdong Chen, Yujian Li:
Priority ordered architecture of neural networks. 808-811 - Thomas Martini Jørgensen, Christian Linneberg:
Boosting the performance of weightless neural networks by using a postprocessing transformation of the output scores. 812-816 - Peter Andras:
Approximation of chaotic shapes with tree-structured neural networks. 817-820 - Jaime Dávila:
Genetic optimization of NN topologies for the task of natural language processing. 821-826 - Yong-Woon Kim, Dong-Jo Park:
Nonlinear channel equalization using new neural network model. 827-830 - Katya O. Gorbunova:
Algorithmically universal model of structureless parallelism. 831-835 - Patricia Pelle, Carlos E. D'Attellis:
Performance improvement of the BSB model in classifier tasks using optimization techniques. 836-840 - De-Shuang Huang:
On the conditions of outer-supervised feedforward neural networks for null cost learning. 841-845 - Tony Jan, Anthony Zaknich:
An adjustable model for linear to nonlinear regression. 846-850 - N. Lighttowler, A. R. Allen, H. Grant, D. C. Hendry, C. T. Spracklen:
The modular map. 851-856 - Marizete Silva Santos, Teresa Bernarda Ludermir:
Using factorial design to optimise neural networks. 857-861 - Radu Dogaru, Marinel Alangiu, Matthias Rychetsky, Manfred Glesner:
Perceptrons revisited: the addition of a non-monotone recursion greatly enhances their representation and classification properties. 862-867 - Lucian N. Vintan, Mihaela Iridon:
Towards a high performance neural branch predictor. 868-873 - Elizabeth C. Behrman, James Edward Steck, Steven R. Skinner:
A spatial quantum neural computer. 874-877
Independent and Principal Component Analysis and Support Vector Machine (Special Session)
- Mikko Lehtokangas:
Inverse PCA method for weight initialization in CMLP network. 878-881 - Juha Karhunen, Simona Malaroiu:
Locally linear independent component analysis. 882-887 - Xavier Giannakopoulos, Juha Karhunen, Erkki Oja:
A comparison of neural ICA algorithms using real-world data. 888-893 - Aapo Hyvärinen, Razvan Cristescu, Erkki Oja:
A fast algorithm for estimating overcomplete ICA bases for image windows. 894-899 - Johan A. K. Suykens, Joos Vandewalle:
Multiclass least squares support vector machines. 900-903 - Kristin P. Bennett, Donghui Wu, Leonardo Auslender:
On support vector decision trees for database marketing. 904-909 - Hsiao-Chun Wu, José C. Príncipe, John G. Harris, Jui-Kuo Juan:
Loss function for blind source separation-minimum entropy criterion and its generalized anti-Hebbian rules. 910-915 - Cynthia Archer, Todd K. Leen:
Optimal dimension reduction and transform coding with mixture principal components. 916-920 - Omid S. Jahromi, Bruce A. Francis:
An information theoretic method for designing multiresolution principal component transforms. 921-926 - Shotaro Akaho, Yasuhiko Kiuchi, Shinji Umeyama:
MICA: multimodal independent component analysis. 927-932 - Yasunori Nishimori:
Learning algorithm for independent component analysis by geodesic flows on orthogonal group. 933-938 - Davide Anguita, Andrea Boni, Sandro Ridella:
A VLSI friendly algorithm for support vector machines. 939-942 - James Tin-Yau Kwok:
Moderating the outputs of support vector machine classifiers. 943-948 - Lei Xu:
Temporal BYY learning and its applications to extended Kalman filtering, hidden Markov model, and sensor-motor integration. 949-954 - Yiu-Ming Cheung, Lei Xu:
An ICA algorithm with adaptive-learned polynomial nonlinearity for signal separation. 955-960 - Yiu-Ming Cheung, Lei Xu:
Autoregressive signal separation approach with seesaw-mapping technique on temporal source separation. 961-964 - Ping Guo, Lei Xu:
On the study of BKYY cluster number selection criterion for small sample data set with bootstrap technique. 965-968 - Matthias Rychetsky, Stefan Ortmann, Manfred Glesner:
Support vector approaches for engine knock detection. 969-974 - Roberto Tagliaferri, Angelo Ciaramella, Leopoldo Milano, Fabrizio Barone:
Hybrid neural networks for frequency estimation of unevenly sampled data. 975-979 - Konstantinos I. Diamantaras, Athina P. Petropulu:
Adaptive blind MIMO system identification using principal component neural models. 980-984 - Simone G. O. Fiori, Pietro Burrascano:
'Mechanical' neural learning and InfoMax orthonormal independent component analysis. 985-988 - Andrew D. Back, Thomas Trappenberg:
Input variable selection using independent component analysis. 989-992 - Mitsuru Kawamoto, Kiyotoshi Matsuoka, Noboru Ohnishi:
Real world blind separation of convolved speech signals. 993-997 - Matthias Rychetsky, Stefan Ortmann, Michael Ullmann, Manfred Glesner:
Accelerated training of support vector machines. 998-1003 - Hamid Eghbalnia, Amir H. Assadi, John D. Carew:
Nonlinear methods for clustering and reduction of dimensionality. 1004-1009 - Amir H. Assadi, Hamid Eghbalnia, John D. Carew:
Local-to-global topological methods in data analysis and applications to fMRI of human brain. 1010-1015 - Annie Xin Guan, Harold H. Szu:
A local face statistics recognition methodology beyond ICA and/or PCA. 1016-1021 - Mohammed Ameen, Harold H. Szu:
Early vision image analyses using ICA in unsupervised learning ANN. 1022-1027 - M. Johnson:
Implementing neural networks into modern technology. 1028-1032 - Zvi Markowitz, Harold H. Szu:
Blind de-mixing real-time algorithm of piecewise time series mixture. 1033-1037 - Noriaki Suetake, Yuu Nakamura, Takeshi Yamakawa:
Maximum entropy ICA constrained by individual entropy maximization employing self-organizing maps. 1038-1042 - Chanchal Chatterjee, Zhengjiu Kang, Vwani P. Roychowdhury:
Adaptive algorithms for accelerated PCA from an augmented Lagrangian cost function. 1043-1048 - Harold H. Szu:
Thermodynamics proof of sensory learning and implication of mammal homeostasis. 1049-1053 - José C. Príncipe, Hsiao-Chun Wu:
Blind separation of convolutive mixtures. 1054-1058
Independent and Principal Component Analysis and Support Vector Machine (Special Session)
- Aapo Hyvärinen, Patrik O. Hoyer:
Independent subspace analysis shows emergence of phase and shift invariant features from natural images. 1059-1064 - Xuhui Shao, Vladimir Cherkassky:
Multi-resolution support vector machine. 1065-1070 - Lei Xu:
Temporal Bayesian Ying-Yang dependence reduction, blind source separation and principal independent components. 1071-1076
Unsupervised Learning
- Sooyong Choi, Daesik Hong:
Performance of RBF equalizer in data storage channels. 1077-1080 - Wai-Keung Fung, Yun Hui Liu:
A game-theoretic formulation on adaptive categorization in ART networks. 1081-1086 - Kunihiko Fukushima:
Self-organization of shift-invariant receptive fields. 1087-1091 - Sylvain Chartier, Robert Proulx:
A self-scaling procedure in unsupervised correlational neural networks. 1092-1096 - Yuhui Yao, Lihen Chen, Yan Qiu Chen:
Unsupervised curve-based clustering. 1097-1101 - Guilherme De A. Barreto, Aluízio F. R. Araújo:
Unsupervised context-based learning of multiple temporal sequences. 1102-1106 - Kyu-Yu Chang, Joydeep Ghosh:
Probabilistic principal surfaces. 1107-1112 - Weigang Li, Nilton Correia da Silva:
A study of parallel neural networks. 1113-1116 - Simone G. O. Fiori, Pietro Burrascano:
Analytical results on pseudo-polynomial functional-link neural units for blind density shaping. 1117-1120 - Christoph Goller, Marco Gori, Marco Maggini:
Feature extraction from data structures with unsupervised recursive neural networks. 1121-1126 - Moritoshi Yasunaga, Kenichi Tominaga, Jung Hwan Kim:
Parallel self-organization map using multiple stimuli. 1127-1130 - Nanning Zheng, Zhihua Zhang, Gang Shi, Ying Qiao:
Self-creating and adaptive learning of RBF networks: merging soft-competition clustering algorithm with network growth technique. 1131-1135 - Sung Mahn Ahn, Sung Wook Baik:
A cluster analysis based on a regularization method. 1136-1139 - Giuseppe Acciani, R. Caradonna, Ernesto Chiarantoni, Giuseppe Grassi:
A density based membership function for fuzzy clustering. 1140-1143 - Kenji Mizoguchi, Masafumi Hagiwara:
A novel neural network for four-term analogy based on area representation. 1144-1149
Neural Network Evaluations
- Chulhee Lee, Jinwook Go:
Multi-level neural networks. 1150-1153 - Jinwook Go, Chulhee Lee:
Analyzing weight distribution of neural networks. 1154-1157 - Susan B. Garavaglia:
The two spirals benchmark: lessons from the hidden layers. 1158-1163 - Y. W. Tong, K. Y. Michael Wong, Song Li:
A new framework for modeling learning dynamics. 1164-1168 - A. G. Ivakhnenko, Donald C. Wunsch, G. A. Ivakhnenko:
Inductive sorting-out GMDH algorithms with polynomial complexity for active neurons of neural network. 1169-1173 - David A. Medler, David B. McCaughan, Michael R. W. Dawson, Leanne Willson:
When local isn't enough: extracting distributed rules from networks. 1174-1179 - Sarah S. Y. Lam, Alice E. Smith:
Validation of neural networks using hybrid resampling methods. 1180-1184 - Carlos López-Vázquez:
Looking inside the ANN "black box": classifying individual neurons as outlier detectors. 1185-1188 - Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Neural networks input selection by using the training set. 1189-1194 - Stavros J. Perantonis, Vassilis Virvilis:
Dimensionality reduction using a novel neural network based feature extraction method. 1195-1198 - Adrian K. Agogino, Joydeep Ghosh, Cheryl E. Martin:
Visualization of radial basis function networks. 1199-1202 - Katsunari Shibata, Koji Ito:
Gauss-sigmoid neural network. 1203-1208 - Michael N. Vrahatis, George D. Magoulas, Vassilis P. Plagianakos:
Convergence analysis of the Quickprop method. 1209-1214 - John Carney, Padraig Cunningham, Umesh Bhagwan:
Confidence and prediction intervals for neural network ensembles. 1215-1218 - Christian Linneberg, Thomas Martini Jørgensen:
Discretization methods for encoding of continuous input variables for Boolean neural networks. 1219-1224
Supervised Learning I
- Homayoun Valafar, Faramarz Valafar, Okan K. Ersoy:
Parallel, self organizing, consensus neural networks. 1225-1228 - Limin Fu:
A neural network for learning domain rules with precision. 1229-1233 - Limin Fu:
Learning in a quantizable neural network. 1234-1238 - Eiji Mizutani:
Powell's dogleg trust-region steps with the quasi-Newton augmented Hessian for neural nonlinear least-squares learning. 1239-1244 - Eiji Mizutani:
Sample path-based policy-only learning by actor neural networks. 1245-1250 - Shoujue Wang, Jingpu Shi, Chuan Chen, Yujian Li:
Direction-basis-function neural networks. 1251-1254 - Harris Drucker:
Z splitting criterion for growing trees and boosting. 1255-1258 - Mitra Basu, Tin Kam Ho:
The learning behavior of single neuron classifiers on linearly separable or nonseparable input. 1259-1264 - Maria Cristina Felippetto de Castro, Fernando César Comparsi de Castro, Dalton Soares Arantes:
RBF neural networks with centers assignment via Karhunen-Loeve transform. 1265-1270 - Jargalsaihan Batsaihan, Cory Barker:
A comparison of Eclectic learning and Stagger. 1271-1274 - Iyab I. Sakhnini, Michael T. Manry, Hema Chandrasekaran:
Iterative Improvement of trigonometric networks. 1275-1280 - Dingding Chen, Martin T. Hagan:
Optimal use of regularization and cross-validation in neural network modeling. 1281-1286 - Min Jang, Sungzoon Cho:
Ensemble learning using observational learning theory. 1287-1292 - Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
A comparison between two interval arithmetic learning algorithms. 1293-1297 - Jinglu Hu, Kotaro Hirasawa:
Object oriented learning network and its applications. 1298-1301 - Kotaro Hirasawa, Jinglu Hu, Junichi Murata, Chunzhi Jin, Hironobu Etoh, Hironobu Katagiri:
Universal learning networks with varying parameters. 1302-1307 - Junichi Murata, Shinji Itoh, Kotaro Hirasawa:
Size-reducing RBF networks. 1308-1312 - Nojun Kwak, Chong-Ho Choi:
Improved mutual information feature selector for neural networks in supervised learning. 1313-1318
Supervised Learning II
- Jacek Mandziuk, Lokendra Shastri:
Incremental class learning-an approach to longlife and scalable learning. 1319-1324 - Andrew Luk, Sandra Lien:
Rival rewarded and randomly rewarded rival competitive learning. 1325-1328 - Jalal Baghdadchi, Fereshteh Fatehi:
Biofunctionality: a novel learning method for intelligent agents. 1329-1332 - Emad W. Saad, Jai J. Choi, John L. Vian, Donald C. Wunsch:
Efficient training techniques for classification with vast input space. 1333-1338 - Hema Chandrasekaran, Michael T. Manry:
Convergent design of a piecewise linear neural network. 1339-1344 - Herna L. Viktor, Ian Cloete:
Improved generalisation using cooperative learning and rule extraction. 1345-1349 - Andries P. Engelbrecht, Ian Cloete:
Incremental learning using sensitivity analysis. 1350-1355 - Sven Behnke:
Hebbian learning and competition in the neural abstraction pyramid. 1356-1361 - Katheryn Margaret Adeney, Michael J. Korenberg:
Iterative fast orthogonal search algorithm for sparse self-structuring generalized single-layer networks. 1362-1367 - Yasuo Matsuyama, Takayuki Ikeda, Tomoaki Tanaka, Satoshi Furukawa, Naoki Takeda, Takeshi Niimoto:
The α-EM learning and its cookbook: from mixture-of-expert neural networks to movie random field. 1368-1373 - Alexander M. Reznik:
Non-iterative learning for neural networks. 1374-1379 - Minghu Jiang, Xiaoyan Zhu:
A novel fast learning algorithms for time-delay neural networks. 1380-1383 - María José Pérez-Ilzarbe:
Preconditioning method to accelerate neural networks gradient training algorithms. 1384-1388 - Hiroshi Ninomiya, Naoki Kinoshita:
A new learning algorithm without explicit error backpropagation. 1389-1392 - Lai-Wan Chan:
Weighted least square ensemble networks. 1393-1396 - Ryotaro Kamimura:
Mediated and multi-level information processing. 1397-1402 - Ryotaro Kamimura:
Controlling simple structural information to improve generalization performance. 1403-1408
Probabilistic Learning
- D. Randall Wilson, Tony R. Martinez:
Combining cross-validation and confidence to measure fitness. 1409-1414 - Mikko Lehtokangas:
Adaptive training methods for optimal margin classification. 1415-1418 - David J. Miller, Lian Yan:
Approximate maximum entropy joint feature inference for discrete space classification. 1419-1424 - Andrew Luk, Sandra Lien:
Lotto-type competitive learning and its stability. 1425-1428 - Juan Ignacio Arribas, Jesús Cid-Sueiro, Tülay Adali, Aníbal R. Figueiras-Vidal:
Neural networks to estimate ML multi-class constrained conditional probability density functions. 1429-1432 - Hongmei Ni, Tülay Adali, Bo Wang:
A general formulation for learning multi-class posterior probabilities. 1433-1437 - Jouko Lampinen, Paula Litkey, Harri Hakkarainen:
Selection of training samples for learning with hints. 1438-1441 - Takashi Kuroki, Toshiyuki Tanaka, Masao Taki:
Examination of effectiveness of higher-order mean field Boltzmann machine learning based on linear response theorem. 1442-1445 - Anthony Zaknich:
Efficient kernel functions for the general regression and modified probabilistic neural networks. 1446-1449 - Alan M. N. Fu, Hong Yan:
A dynamic mapping based on probabilistic relaxation. 1450-1455 - Hujun Yin, Nigel M. Allinson:
Averaging ensembles of self-organising mixture networks for density estimation. 1456-1460 - Xiongfeng Feng, Xianhui Yang, Yongmao Xu:
A new method for density estimation by using forward neural network. 1461-1464 - Jefferson M. Willey, Harold Szu, Mona E. Zaghloul:
Conditional entropy minimization in neural network classifiers. 1465-1470
Recurrent Neural Networks
- Mikko Lehtokangas:
On weight initialization in cascade-correlation learning. 1471-1474 - Ivelin Stoianov:
Recurrent auto-associative networks and sequential processing. 1475-1480 - Johan A. K. Suykens, Joos Vandewalle:
Continuous time NLq theory: absolute stability criteria. 1481-1484 - Dong-Chul Park, Tae-Kyun Jung Jeong:
Complex bilinear recurrent neural network for equalization of a digital satellite channel. 1485-1490 - Khalid Al-Mashouq, Yousif Al-Hodaif:
Optimization of recursive branching network. 1491-1495 - Meng H. Fun, Martin T. Hagan:
Recursive orthogonal least squares learning with automatic weight selection for Gaussian neural networks. 1496-1500 - Euripedes P. dos Santos, Fernando J. Von Zuben:
Improved second-order training algorithms for globally and partially recurrent neural networks. 1501-1506 - S. A. Terekhoff, N. N. Fedorova:
Cascade neural networks in variational methods for boundary value problems. 1507-1510 - Tracey Ann Bale, Khurshid Ahmad:
A partially recurrent mixture-of-experts model for task decomposition into temporal and static subtasks. 1511-1514 - Ashraf M. Abdelbar, Murad Assaggaf:
Recurrent high-order networks for probabilistic explanation. 1515-1520 - Lai-Wan Chan, Chi-Cheong Szeto:
Training recurrent network with block-diagonal approximated Levenberg-Marquardt algorithm. 1521-1526 - Mikel L. Forcada, Antonio M. Corbí-Bellot, Marco Gori, Marco Maggini:
Recurrent neural networks can learn simple, approximate regular languages. 1527-1532
Learning in Time Series
- Ernst Haselsteiner:
Dynamic targets - adapting supervised learning to time series classification. 1533-1537 - Ajoy Kumar Palit, Dobrivoje Popovic:
Forecasting chaotic time series using neuro-fuzzy approach. 1538-1543 - Pu Sun, Kenneth A. Marko:
A gain perturbation method to improve the generalization performance for the recurrent neural network misfire detector. 1544-1549 - Vladimir Chinarov, Martin Dudziak, Michael Menzinger, Yuri Kyrpach:
Pattern recognition and learning in bistable CAM networks. 1550-1553 - Man-chung Chan, Chi-Chung Fung:
Incremental adaptation of resource-allocating network for non-stationary time series. 1554-1559 - Juan Ignacio Arribas, Jesús Cid-Sueiro, Tülay Adali, Hongmei Ni, Bo Wang, Aníbal R. Figueiras-Vidal:
Estimates of constrained multi-class a posteriori probabilities in time series problems with neural networks. 1560-1561 - William D. Penny, Stephen J. Roberts:
Dynamic logistic regression. 1562-1567 - David A. Calvert, Deborah A. Stacey:
Components for a sequence processing neural network. 1568-1573 - William H. Hsu, Sylvian R. Ray:
Construction of recurrent mixture models for time series classification. 1574-1579 - Roger L. Schultz, Martin T. Hagan, Orlando De Jesus:
Training multi-loop networks. 1580-1585 - Minghu Jiang, Xiaoyan Zhu:
A robust learning algorithm for the extended AM neural network. 1586-1589 - Ashraf A. M. Khalaf, Kenji Nakayama:
A learning algorithm for a hybrid nonlinear predictor applied to noisy nonlinear time series. 1590-1593 - Sherif Hashem, Z. H. Ashour, E. F. Abdel Gawad, A. Abdel Hakeem:
A novel approach for training neural networks for long-term prediction. 1594-1599 - Tuan A. Duong, Taher Daud:
Cascade error projection with low bit weight quantization for high order correlation data. 1600-1603
Multilayer Perceptrons
- Mikko Lehtokangas:
On optimal usage of centroid units in CMLP network. 1604-1607 - Tim Andersen, Tony R. Martinez:
The little neuron that could. 1608-1613 - Tim Andersen, Tony R. Martinez:
Cross validation and MLP architecture selection. 1614-1619 - James T. Lo, Devasis Bassu:
Adaptive multilayer perceptrons. 1620-1625 - James T. Lo:
Initializing multilayer perceptrons with interconnected neurons. 1626-1630 - Mingsheng Zhao, Youshou Wu:
Classification complexity and its estimation algorithm for two-class classification problem. 1631-1634 - Sang-Hoon Oh, Soo-Young Lee:
Optimal learning rates for each pattern and neuron in gradient descent training of multilayer perceptrons. 1635-1638 - Changgeng Xi, Fang Wang, Vijaya Kumar Devabhaktuni, Qi-Jun Zhang:
Huber optimization of neural networks: a robust training method [microwave modeling]. 1639-1642 - Sridhar Narayan:
Enhancing incremental learning in MLP networks using ensemble encoding of network inputs. 1643-1645 - Jean-François Hébert, Marc Parizeau, Nadia Ghazzali:
An hybrid architecture for active and incremental learning: the self-organizing perceptron (SOP) network. 1646-1651 - Kanad Keeni, Kenji Nakayama, Hiroshi Shimodaira:
Estimation of initial weights and hidden units for fast learning of multilayer neural networks for pattern classification. 1652-1656 - Kenji Nakayama, Akihiro Hirano, Issei Ido:
A multilayer neural network with nonlinear inputs and trainable activation functions: structure and simultaneous learning algorithm. 1657-1661 - Aki Vehtari, Jouko Lampinen:
Bayesian neural networks with correlating residuals. 1662-1665 - B. R. Linnell:
Quadrant-distance graphs: a method for visualizing neural network weight spaces. 1666-1671
Multilayer Pereptrons
- Octavian Stan, Edward W. Kamen:
New block recursive MLP training algorithms using the Levenberg-Marquardt algorithm. 1672-1677 - James T. Lo:
Statistical method of pruning neural networks. 1678-1680 - Zhen Zhang, Weimin Shao, Hong Zhang:
A learning algorithm for multilayer perceptron as classifier. 1681-1684 - Yunho Jeon, Chong-Ho Choi:
Thermometer coding for multilayer perceptron learning on continuous mapping problems. 1685-1690 - Rohit Lotlikar, Ravi Kothari:
Multilayer perceptron based dimensionality reduction. 1691-1695 - Peter B. Luh, Li Zhang:
A novel neural learning algorithm for multilayer perceptrons. 1696-1701
Backpropagation
- Jun-Qing Chen, Jing-ping Jiang:
New methods to train a BP network and their application. 1702-1705 - Mikko Lehtokangas:
Improved CBP learning with output bias decomposition. 1706-1709 - Nathalie Japkowicz, Stephen Jose Hanson:
Adaptability of the backpropagation procedure. 1710-1715 - Dongxin Xu, José C. Príncipe:
Training MLPs layer-by-layer with the information potential. 1716-1720 - Chulhee Lee, Jinwook Go:
Multi-gradient: a fast converging and high performance learning algorithm. 1721-1724 - Bogdan M. Wilamowski, Yixin Chen, Aleksander Malinowski:
Efficient algorithm for training neural networks with one hidden layer. 1725-1728 - Bin-Chul Ihm, Dong-Jo Park:
Acceleration of learning speed in neural networks by reducing weight oscillations. 1729-1732 - Peitsang Wu, Shu-Cherng Fang, Henry L. W. Nuttle:
Curved search algorithm for neural network learning. 1733-1736 - Hahn-Ming Lee, Tzong-Ching Huang, Chih-Ming Chen:
Learning efficiency improvement of back propagation algorithm by error saturation prevention method. 1737-1742 - Daniel Volovici, Adrian Mihalache, Mihaela Iridon, Macarie Breazu:
A new backpropagation learning algorithm. 1743-1748 - Jan Wilk, Eva Wilk, Holger Gobel:
ACL-adaptive correction of learning parameters for backpropagation based algorithms. 1749-1752 - Yingyang Lu, Shenchu Xu, Boxi Wu, Zhenxiang Chen:
Pattern grouping strategy makes BP algorithm less sensitive to learning rate. 1753-1756 - José B. Galván:
A new adaptive scheme for the backpropagation algorithm. 1757-1761 - Vassilis P. Palgianakos, Michael N. Vrahatis, George D. Magoulas:
Nonmonotone methods for backpropagation training with adaptive learning rate. 1762-1767 - George D. Magoulas, Vassilis P. Plagianakos, Michael N. Vrahatis:
Sign-methods for training with imprecise error function and gradient values. 1768-1773 - Gustavo Guimarães Parma, Benjamin Rodrigues de Menezes, Antônio de Pádua Braga:
Sliding mode backpropagation: control theory applied to neural network learning. 1774-1778 - B. V. S. Murthy:
Delta learning law for a single neuron. 1779-1782 - José C. Príncipe, Dongxin Xu:
An introduction to information theoretic learning. 1783-1787
Feedforward Networks
- Z. P. Liu, J. P. Castagna:
Avoiding overfitting caused by noise using a uniform training mode. 1788-1793 - Edmondo Trentin:
Activation functions with learnable amplitude. 1794-1798 - Tasos Falas, Andreas-Georgios Stafylopatis:
The impact of the error function selection in neural network-based classifiers. 1799-1804 - Wangchao Li, Yongbin Yang, Jie Zhang, Liyang Wang:
Sparse algorithm for feed-forward neural networks. 1805-1808 - Gintaras V. Puskorius, Lee A. Feldkamp:
Roles of learning rates, artificial process noise and square root filtering for extended Kalman filter training. 1809-1814 - Akira Hirabayashi, Gintaras Ogawa:
A class of learning for optimal generalization. 1815-1819 - Hong Zhang, Zhen Zhang:
Feedforward networks with monotone constraints. 1820-1823 - Harry C. S. Rughooputh, S. D. D. V. Rughooputh:
Extended Kalman filter learning algorithm for hyper-complex multilayer neural networks. 1824-1828 - Andries P. Engelbrecht, L. Fletcher, Ian Cloete:
Variance analysis of sensitivity information for pruning multilayer feedforward neural networks. 1829-1833 - Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Input selection by multilayer feedforward trained networks. 1834-1839 - Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
Generalization capability of one and two hidden layers. 1840-1843 - Jonathan P. Lewis, Michael K. Weir:
Subgoal chaining and the local minimum problem. 1844-1849 - Nikolaos Ampazis, Stavros J. Perantonis, John G. Taylor:
Acceleration of learning in feedforward networks using dynamical systems analysis and matrix perturbation theory. 1850-1855 - María M. Abad-Grau, L. Daniel Hernandez Molinero:
Feature selection in codebook based methods provides high accuracy. 1856-1860 - Nigel Duffy:
Using multiplicative algorithms to build cascade correlation networks. 1861-1865 - Fabrice Bossaert, Didier Benjamin:
AINS: architecture independent neuron selection. 1866-1869 - Roger L. Schultz, Martin T. Hagan:
Online least-squares training for the underdetermined case. 1870-1875 - Christelle Godin, Jean-Dennis Muller, Mitra B. Gordon, J. Haussy:
Pattern recognition with spiking neurons: performance enhancement based on a statistical analysis. 1876-1880 - Andreas Wendemuth, Michael Gerke:
Optimal training parameters in multilayer feedforward networks. 1881-1884 - Shenghong Li, Zemin Liu:
A general CAC approach using novel ant algorithm training based neural network. 1885-1888 - Gou-Jen Wang, Jai-Juin Chen:
Cascade steepest descent learning algorithm for multilayer feedforward neural network. 1889-1894 - G. M. Donnelly, P. C. Ojha, David A. Bell:
Growing smaller networks with the tiling algorithm. 1895-1899
Self-Organizing Maps
- Panu Somervuo:
Time topology for the self-organizing map. 1900-1905 - Mu-Chun Su, Ta-Kang Liu, Hsiao-Te Chang:
An efficient initialization scheme for the self-organizing feature map algorithm. 1906-1910 - Jouko Lampinen, Timo Kostiainen:
Overtraining and model selection with the self-organizing map. 1911-1915 - Leandro Nunes de Castro, Fernando J. Von Zuben:
An improving pruning technique with restart for the Kohonen self-organizing feature map. 1916-1919 - Takeo Yamada, Motonobu Hattori, Masayuki Morisawa, Hiroshi Ito:
Sequential learning for associative memory using Kohonen feature map. 1920-1923 - Ian R. Fasel, Kurt D. Bollacker, Joydeep Ghosh:
A neural network based classifier and biofeedback device for improving clarinet tone-quality. 1924-1928 - Ming-Hsuan Yang, Narendra Ahuja:
A data partition method for parallel self-organizing map. 1929-1933 - Paul Hannah, Russel J. Stonier, Cilin Cole:
Approximating rail locomotive dynamics using the SOCM network. 1934-1938 - Mohummad B. Menhaj, Hamid R. Jahanian:
An analytical alternative for SOM. 1939-1942 - Mêuser J. S. Valença, Teresa Bernarda Ludermir:
Self-organization sigmoidal blocks networks. 1943-1946 - Daniel Kottow, Javier Ruiz-del-Solar:
A new neural network model for automatic generation of Gabor-like feature filters. 1947-1952 - Russell Keith-Magee, Svetha Venkatesh, Masahiro Takatsuka:
An empirical study of neighbourhood decay in Kohonen's self organising map. 1953-1958 - Lia Caetano Bastos, Rogério Cid Bastos, Waleska Nishida:
Radial basis function for classification of remote sensing images. 1959-1962 - Dae Yup Lee, Byung Man Kim, Hyung Suck Cho:
A self-organizing radial basis function network combined with ART II. 1963-1968 - Mu-Chun Su, I-Chen Liu:
Facial image morphing by self-organizing feature maps. 1969-1972
ART
- Penny Pei Chen, Wei-Chung Lin, Hai-Lung Hung:
Multi-resolution fuzzy ART neural networks. 1973-1978 - Thomas P. Caudell, Michael J. Healy:
Studies of generalization for the LAPART-2 architecture. 1979-1982 - Gail A. Carpenter, Boriana L. Milenova:
Distributed ARTMAP. 1983-1987 - Pierre Lavoie:
Choosing a choice function: granting new capabilities to ART. 1988-1993
Robotic Control
- Jae Heon Chung, Steven A. Velinsky:
Intelligent reconfigurable control of robot manipulators. 1994-1998 - Jose Antonio Heredia Huerta, Wen Yu:
A modified PD control of robot manipulator using neural network compensator. 1999-2004 - Wai Sum Tang, Jun Wang:
An improved neurocomputation scheme for minimum infinity-norm kinematic control of redundant manipulators. 2005-2010 - Michail G. Lagoudakis, Anthony S. Maida:
Neural maps for mobile robot navigation. 2011-2016 - Sang-Hee Kim, Su-Dong Hong, Chang-Hyun Chai, Won Woo Park:
A design of prefilter type compensatory controller for robot manipulator using modified chaotic neural networks. 2017-2020 - John E. Lecky:
Using scout clusters for motion planning. 2021-2025 - Alexander A. Bogdanov, Adil Vassilyevich Timofeev:
Robust optimal neural control of robots. 2026-2031 - Dong-Sun Park, Sok Yoon, YoungBu Kim:
Robot end-effector recognition using modular neural network for autonomous control. 2032-2036 - Ozgur Ozan Gurun:
Dynamic coordination of multi-robots by Bayesian modeling. 2037-2042 - John Weissmann, Ralf Salomon:
Gesture recognition for virtual reality applications using data gloves and neural networks. 2043-2046 - Ralf Salomon:
Online adaptation in autonomous robots by using proprioceptive feedback. 2047-2050 - Kentaro Mizutani, Takashi Omori:
Online map formation and path planning for mobile robot by associative memory with controllable attention. 2051-2056 - Simone G. O. Fiori, Alessandro Faustini, Pietro Burrascano:
Non-uniform image sampling for robot motion control by the GFS neural algorithm. 2057-2060 - Roman Genov, Srinadh Madhavapeddi, Gert Cauwenberghs:
Learning to navigate from limited sensory input: experiments with the Khepera microrobot. 2061-2064 - Eimei Oyama, Susumu Tachi:
Inverse kinematics learning by modular architecture neural networks. 2065-2070 - Claude F. Touzet:
Programming robots with associative memories. 2071-2075
Nonlinear Control
- Kyungmoon Nho, Ramesh K. Agarwal:
Adaptive control of aircraft dynamics using neural networks. 2076-2080 - Wen Yu, Alexander S. Poznyak:
System identification with partial-state measurement via dynamic multilayer neural networks. 2081-2086 - Jim Benjamin Luther, Paul Haase Sorensen:
Stability of a neural predictive controller scheme on a neural model. 2087-2091 - Dan Wang, Jie Huang:
Solving discrete-time nonlinear servomechanism problem with feedforward neural networks. 2092-2097 - Andrzej Dzielinski:
Neural networks based NARX models in nonlinear adaptive control. 2098-2103 - Jin-Tsong Jeng, Tsu-Tian Lee:
An approximate equivalence neural network to conventional neural network for the worst-case identification and control of nonlinear system. 2104-2108 - Edgar N. Sánchez, Alexander S. Poznyak, Wen Yu:
Dynamic multilayer neural network for nonlinear system identification. 2109-2113 - Edgar N. Sánchez, Miguel A. Bernal:
Nonlinear system adaptive trajectory tracking by dynamic neural control. 2114-2118 - Carlos Pinheiro, Fernando A. C. Gomide:
Neural control of nonlinear systems by frequency response. 2119-2122 - Kotaro Hirasawa, Jinglu Hu, Junichi Murata, Chunzhi Jin, Kazuaki Yotsumoto, Hironobu Katagiri:
Identification of nonlinear dynamic systems by using probabilistic universal learning networks. 2123-2128 - Heidar A. Talebi, Khashayar Khorasani, Rajni V. Patel:
Experimental results on neural network-based control strategies for flexible-link manipulators. 2129-2134 - K. P. Dimopoulos, C. Kambhampati:
Multiple interconnected Hopfield networks for intelligent global linearising control. 2135-2140 - Kurosh Madani, Abdennasser Chebira, Jean-Charles Depecker, Gilles Mercier:
An intelligent adaptive vector control technique using a multi-neural networks based hybrid structure. 2141-2145 - Kiyotaka Shimizu, Kazuyuki Ito:
Design of neural stabilizing controller for nonlinear systems via Lyapunov's direct method. 2146-2151 - Rémi Munos, Leemon C. Baird III, Andrew W. Moore:
Gradient descent approaches to neural-net-based solutions of the Hamilton-Jacobi-Bellman equation. 2152-2157 - Ganesh K. Venayagamoorthy, Ronald G. Harley:
Experimental studies with a continually online trained artificial neural network controller for a turbogenerator. 2158-2163
Robust Artificial Neural Network Controllers
- Yusuke Kurita, Tsuyoki Hashimoto, Yoshihisa Ishida:
An application of time delay estimation by ANNs to frequency domain adaptive I-PD controller. 2164-2167 - Yujin Luo, Shoujue Wang:
The real time emulation of artificial neural network control system. 2168-2171 - Hiroaki Nakanishi, Koichi Inoue:
Training method for a sliding mode controller and quantified robustness against uncertainty. 2172-2177 - Frederick L. Crabbe, Michael G. Dyer:
Second-order networks for wall-building agents. 2178-2183 - Yutczka Maeda, Kouji Kawaguchi:
Neurocontroller for unknown systems using simultaneous perturbation. 2184-2187 - Arto Visala, Hannu Pitkänen, Janne Paanajärvi:
Wiener-NN models and robust identification. 2188-2193 - Gon-Jen Wang, Tzong-Jing Lee:
Neural-network cross-coupled control system with application on circular tracking of linear motor X-Y table. 2194-2199 - Maurício José Bordon, Celso Pascoli Bottura, Marcelo Carvalho Minhoto Teixeira:
Quasi-invariant stable multivariable CMAC variable structure neurocontrol. 2200-2203 - Amir Karniel, Ron Meir, Gideon F. Inbar:
Exploiting the virtue of redundancy. 2204-2209
Genetic, Neural, and Fuzzy Controller
- Hyung-Soo Hwang, Jeoung-Nae Choi, Won-Hyok Lee, Jin Kwon Kim:
A tuning algorithm for the PID controller utilizing fuzzy theory. 2210-2215 - Peggy Israel Doerschuk, Eric Sarrafian:
Conventional vs. RBF control of a benchmark process control problem. 2216-2219 - Fenurndo Lara-Rojo, Edgar N. Sánchez, Erik Valdemar Cuevas Jiménez:
Real-time neurofuzzy control for an underactuated robot. 2220-2225 - Alireza Khotanzad, Hassan M. Elragal, Clark Kinnaird:
Neural network based process control of integrated circuit wire bonding machine. 2226-2229 - Raja Shahid Toqeer, N. Suha Bayindir:
Fast training of an MLP based neurocontroller using EBUDS. 2230-2235 - Yakov Frayman, Lipo Wang:
Direct MRAC with dynamically constructed neural controllers. 2236-2240 - Kenneth J. Mackin, Eiichiro Tazaki:
Emergence of group behavior in multiagent systems using self trained agent communication. 2241-2244 - Chih-Chi Chang, Chungyong Tsai:
A neural-fuzzy controller with heterogeneous neurons. 2245-2248 - Chungyong Tsai, Chih-Chi Chang:
A neural network controller based on the rule of bang-bang control. 2249-2252
Reinforcement Learning
- Ron Sun, Chad Sessions:
Self-segmentation of sequences. 2253-2258 - Ron Sun, Todd Peterson:
Partitioning in reinforcement learning. 2259-2264 - George G. Lendaris, Thaddeus T. Shannon, Andres Rustan:
A comparison of training algorithms for DHP adaptive critic neurocontrol. 2265-2270 - Thaddeus T. Shannon:
Partial, noisy and qualitative models for adaptive critic based neurocontrol. 2271-2275 - Relu Patrascu, Deborah Stacey:
Adaptive exploration in reinforcement learning. 2276-2281 - William Ward Armstrong, Brant Coghlan, Dmitry O. Gorodnichy:
Reinforcement learning for autonomous robot navigation. 2282-2287 - Chengan Guo, Anthony Kuh:
A neural-network Q-learning method for decentralized sequential detection with feedback. 2288-2291 - Paul J. Werbos:
New designs for universal stability in classical adaptive control and reinforcement learning. 2292-2295
Artificial Systems - Network Implementation
- Geoffrey L. Barrows, Kurt T. Miller, Brian Krantz:
Fusing neuromorphic motion detector outputs for robust optic flow measurement. 2296-2301 - M. Diepenhorst, Martijn van Veelen, J. A. G. Nijhuis, Lambert Spaanenburg:
Automatic generation of VHDL code for neural applications. 2302-2305 - Bogdan M. Wilamowski, Don L. Jordan:
A synchronous high-speed, high-accuracy, loser-take-all circuit. 2306-2309 - Eric L. Brown, Bogdan M. Wilamowski:
Spatial to temporal conversion of images using a pulse-coupled neural network. 2310-2314 - Elizabeth J. Brauer, James J. Abbas, Brian Callaway, Joshua Colvin, John Farris:
Hardware implementation of a neural network pattern shaper algorithm. 2315-2318 - Eric J. Brauer, Ranu Jung, Brett Thompsen, James J. Abbas:
A VLSI circuit of lamprey unit pattern generator. 2319-2322 - Jin Liu, Martin A. Brooke:
A fully parallel learning neural network chip for real-time control. 2323-2328 - Zaven K. Kalayjian, Andreas G. Andreou:
A silicon retina for polarization contrast vision. 2329-2332 - Philippe O. Pouliquen, Andreas G. Andreou, Gert Cauwenberghs, Conrad W. Terrill:
Learning to compensate for sensor variability at the focal plane. 2333-2336 - Chiou-Ling Yeh, Chung-Yu Wu:
The design of CMOS cellular neural network (CNN) using the neuron-bipolar junction transistor (νBJT). 2337-2342 - Marc Cohen, R. Timothy Edwards, Gert Cauwenberghs, Mikhail A. Vorontsov, Gary Carhart:
AdOpt: analog VLSI stochastic optimization for adaptive optics. 2343-2346 - Mitsunaga Kinjo, Shigeo Sato, Koji Nakajima:
A study on DBM network with non-monotonic neurons. 2347-2350 - Steven R. Skinner, James Edward Steck, Alvaro A. Cruz-Cabrara, Mingtao Yang, Elizabeth C. Behrman:
Optical hardware backpropagation neural network. 2351-2356 - Alexandre Schmid, Yusuf Leblebici, Daniel Mlynek:
A two-stage charge-based analog/digital neuron circuit with adjustable weights. 2357-2362
Network Analysis
- Francisco Javier López Aligué, Carlos J. García Orellana, M. Isabel Acevedo Sotoca, Horacio M. González Velasco, Miguel Macías Macías:
Modelling and simulation of large neural networks. 2363-2367 - Xiaoou Li, Felipe Lara-Rosano:
A weighted fuzzy petri net model for knowledge learning and reasoning. 2368-2372 - Anatoli Gorchetchinikov:
Limitations on the connection weights due to the introduction of threshold self-adjustment. 2373-2377 - N. N. Fedorova, S. A. Terekhoff:
Parallel MPI implementation of training algorithms for medium-size feedforward neural networks. 2378-2379 - Ismael Espinosa, Ritaluz Lara, Joel Jimenez:
Simulation model for locomotion in mobile legged robots that includes optimization and associative memory. 2380-2385 - Minho Lee, Sang-Woo Ban, Jun-Ki Cho, Chang-Jin Seo, Soon Ki Jung:
Modeling of saccadic movements using neural networks. 2386-2389 - Taiji Satoh, Akihiko Uchibori, Kanya Tanaka:
Artificial life system for optimization of nonconvex functions. 2390-2393 - Shivakumar Viswanathan, Ilker Ersoy, Filiz Bunyak, Cihan H. Dagli:
Evolving neural networks applied to predator-evader problem. 2394-2397 - M. Giacinti, G. Latini, Paolo Campolucci, Francesco Piazza:
A CAD approach to the design of a neural network simulator. 2398-2401 - Teru Yoneyama, Hiroshi Ninomiya, Hideki Asai:
Design method of neural networks for limit cycle generator. 2402-2405 - Anthony Kuh:
Performance of analog neural networks subject to drifting targets and noise. 2406-2409 - Alexandra I. Cristea, Toshio Okamoto:
Speed-up opportunities for ANN in a time-share parallel environment. 2410-2413
Digital Network
- James J. Buckley, Thomas Feuring, Yoichi Hayashi:
Neural nets, fuzzy and crisp, in the design of an artificial agent. 2414-2418 - Sorin Draghici, Damon A. Miller:
A VLSI neural network classifier based on integer-valued weights. 2419-2424 - Takamichi Nakamoto, S. Kawamura, Toyosaka Moriizumi:
Study of digital learning circuit for odor sensing system using 1-bit data stream signal processing circuit. 2425-2428 - Guoxing Li, Bingxue Shi:
A current-mode programmable and expandable Hamming neural network. 2429-2432 - Kurosh Madani, Dominique Degeest, Nabil Mesbah:
A hybrid approach for image half-toning combining simulated annealing and neural networks based techniques: implementation on a zero instruction set computer based neural machine. 2433-2436 - Thitipong Tamprasert, Pham Hong Hanh:
An efficient approach to engage neural net hardware to PC. 2437-2440 - Yann Boniface, Frédéric Alexandre, Stéphane Vialle:
A bridge between two paradigms for parallelism: neural networks and general purpose MIMD computers. 2441-2446 - Fumihiro Hatano, Noriko Akita, Kiyotaka Komoku, Takayuki Morishita, Iwao Teramoto:
Implementation of cell array neuro-processor by using FPGA. 2447-2451 - Noriko Akita, Fumihiro Hatano, Kiyotaka Komoku, Takayuki Morishita, Iwao Teramoto:
Development support software of cell array processor and its neural network application. 2452-2455 - Mário Eduardo Bordon, Ivan Nunes da Silva, André Nunes de Souza:
Design of digital PID controller with gain planning based on CMAC. 2456-2460 - Marcelo M. de Barros, Jeferson L. F. Valadares, Teresa Bernarda Ludermir:
Rule extraction from Boolean artificial neural networks. 2461-2465 - Steven C. Suddarth:
Domain-specific processing - building a digital/analog neural processing system for control of intelligent robotics. 2466-2469
Self-Organization in Data Mining
- Jorma Laaksonen, Markus Koskela, Erkki Oja:
PicSOM: self-organizing maps for content-based image retrieval. 2470-2473 - Slobodan Vucetic, Tim Fiez, Zoran Obradovic:
A data partitioning scheme for spatial regression. 2474-2479 - William H. Hsu, Loretta S. Anvil, William M. Pottenger, David Tcheng, Michael Welge:
Self-organizing systems for knowledge discovery in large databases. 2480-2485 - Rainer Telesko, Dimitris Karagiannis:
Knowledge selection with neural networks. 2486-2489 - Yakov Frayman, Kai Ming Ting, Lipo Wang:
A fuzzy neural network for data mining: dealing with the problem of small disjuncts. 2490-2493 - Kenneth J. McGarry, Stefan Wermter, John MacIntyre:
Knowledge extraction from radial basis function networks and multilayer perceptrons. 2494-2497 - Yue Joseph Wang, Lan Luo, Matthew T. Freedman, Sun-Yuan Kung:
Hierarchical probabilistic principal component subspaces for data visualization. 2498-2503 - Eduardo R. Hruschka, Nelson Francisco Favilla Ebecken:
Rule extraction from neural networks: modified RX algorithm. 2504-2508 - Georgios Lezos, Monte P. Tull, Joseph P. Havlicek, Jim Sluss:
Predicting the future with the appropriate embedding dimension and time lag. 2509-2513 - Luigi Lancieri:
Description of Internet user behavior. 2514-2519 - Lei Xu:
Data mining, unsupervised learning and Bayesian ying-yang theory. 2520-2525
Neural Networks in Data Mining
- Jen-Lun Yuan:
Bootstrapping nonparametric feature selection algorithms for mining small data sets. 2526-2529 - Aleksandar Lazarevic, Xiaowei Xu, Tim Fiez, Zoran Obradovic:
Clustering-regression-ordering steps for knowledge discovery in spatial databases. 2530-2534 - Dragan Obradovic, Zoran Obradovic:
Efficient probability density balancing for supporting distributed knowledge discovery in large databases. 2535-2538 - Eriko Ikeda, Toshio Imaoka, Hidetomo Ichihashi, Tetsuya Miyoshi:
Nonlinear component analysis by fuzzy clustering and multidimensional scaling methods. 2539-2543 - Xiaoqi Li, Irwin King:
Gaussian mixture distance for information retrieval. 2544-2549 - Jeong-Yon Shim, Chong-Sun Hwang:
Data extraction from associative matrix based on selective learning system. 2550-2553 - Ron Sun:
Knowledge extraction from reinforcement learning. 2554-2559
Time Series
- Mikko Lehtokangas:
Time series modelling with recurrent CBP. 2560-2563 - Sheng-Fu Liang, Alvin W. Y. Su, Cheng-Teng Lin:
A new recurrent-network-based music synthesis method for Chinese plucked-string instruments - Pipa and Qin. 2564-2569 - Patrik O. Hoyer, Aapo Hyvärinen:
Estimating signal-adapted wavelets using sparseness criteria. 2570-2575 - Torbjørn Eltoft, Rui J. P. deFigueiredo:
Dynamical-functional neural networks for time series prediction. 2576-2579 - Kristin L. Adair:
Extracting knowledge from temporal clusters for real-time clustering. 2580-2583 - Rhee Man Kil, Seon Hee Park, Seunghwan Kim:
Time series analysis based on the smoothness measure of mapping in the phase space of attractors. 2584-2589 - Jeong-woo Sohn, Byoung-Tak Zhang, Bong-Kiun Kaang:
Temporal pattern recognition using a spiking neural network with delays. 2590-2593 - Michel Crucianu, Romuald Boné, Jean Pierre Asselin de Beauville:
Bayesian learning for time series prediction with exogenous variables. 2594-2599 - Lars Kindermann, Thomas Trappenberg:
Modeling time-varying processes by unfolding the time domain. 2600-2603 - Takashi Matsumoto, Motoki Saito, Junjiro Sugi:
Nonlinear time series prediction weighted by marginal likelihoods: a hierarchical Bayesian approach. 2604-2607 - Sameer Singh:
Neural network separation of temporal data. 2608-2613 - Wlodzimierz Pogribny:
2-D Fourier transformation in mixed formats. 2614-2617 - R. J. Semnani, Baxter F. Womack, J. K. Hayes:
Design of an optimized continuous mini-bolus thermodilution cardiac output monitor using artificial neural networks and genetic algorithms. 2618-2623 - Martijn van Veelen, J. A. G. Nijhuis, Lambert Spaanenburg:
Estimation of linear filter banks for multivariate time series prediction with temporal principal component analysis. 2624-2628 - Shahram Hosseini, Christian Jutten:
Colored noise in dynamic systems: unbiased modeling by constructive neural networks. 2629-2632 - Mark R. Cowper, Bernard Mulgrew:
Nonlinear processing of high resolution radar sea clutter. 2633-2638 - Narada D. Warakagoda, Magne Hallstein Johnsen:
Multilayer perceptron based optimal state space reconstruction for time series modelling. 2639-2642 - Pengyu Hong, Sylvian R. Ray, Thomas S. Huang:
A new scheme for extracting multi-temporal sequence patterns. 2643-2648 - DaeEun Kim, Jaehong Park:
Frequency selection with oscillatory neurons for engine misfire detection. 2649-2652
Image Analysis
- Ke Chen, DeLiang L. Wang:
Image segmentation based on a dynamically coupled neural oscillator network. 2653-2658 - Paul E. Keller, A. David McKinnon:
Segmentation of medical imagery with pulse-coupled neural networks. 2659-2663 - Lei Wang, Feihu Qi:
Adaptive fuzzy Kohonen clustering network for image segmentation. 2664-2667 - Dong-Chul Park, Young-June Woo:
Weighted centroid neural network for edge preserving image compression. 2668-2673 - Mitra Basu, Min Su:
Deblurring images using projection pursuit learning network. 2674-2678 - Xiuwen Liu, DeLiang Wang:
Perceptual organization based on temporal dynamics. 2679-2684 - Mustafa Sakalli, Hong Yan, Alan M. N. Fu:
A fuzzy-Bayesian approach to image expansion. 2685-2689 - Ioannis M. Stephanakis, George Stamou, Stefanos D. Kollias:
Piecewise Wiener filter model based on fuzzy partition of local wavelet features for image restoration. 2690-2693 - Macarie Breazu, Gavril Toderean, Daniel Volovici, Mihaela Iridon:
Speeding up fractal image compression by working in Karhunen-Loeve transform space. 2694-2697 - Qian Du, Chein-I Chang:
An interference rejection-based radial basis function neural network for hyperspectral image classification. 2698-2703 - Raymond K. Chafin, Cihan H. Dagli:
A biologically inspired connectionist model for image feature extraction in 2D pattern recognition. 2704-2709 - Keiichi Horio, Takuma Haraguchi, Takeshi Yamakawa:
An intuitive contrast enhancement of an image data employing the self-organizing relationship (SOR). 2710-2714 - Vitali V. Gavrik:
Properties of taking-decision function in psychophysical tests. 2715-2718 - Yongtae Do:
Application of neural networks for stereo-camera calibration. 2719-2722 - Erdogan Çesmeli, DeLiang Wang:
Image segmentation based on motion/luminance integration and oscillatory correlation. 2723-2728 - Roger Cozien, Ronan Querrec, Frederick Douchet, Fabrice Lopin:
Neural networks to depict the knowledge of multi-agents systems: application to image processing. 2729-2734 - Mu-Song Chen, Fong Hang Liao:
Genetic learning of neural networks and its applications. 2735-2740 - Nabeel Murshed:
A neural network structure for detecting straight line segments. 2741-2746 - A. N. Rajagopalan, Philippe Burlina, Rama Chellappa:
Detection of people in images. 2747-2752 - Kaori Yoshida, Toshikazu Kato, Torao Yanaru:
Subjective aspects in image database system. 2753-2756
Information Fusion (Special Session)
- Robert J. Abrahart, Linda See:
Fusing multi-model hydrological data. 2757-2762 - Edmond Chin-Ping Chang:
Estimate traffic control patterns using a hybrid neural network. 2763-2767 - De-Shuang Huang:
A fusion design of linear feedforward neural networks for pattern classification. 2768-2771 - Hugh Pasika, Simon Haykin, Eugene E. Clothiaux, Ron Stewart:
Neural networks for sensor fusion in remote sensing. 2772-2776 - Lovell Hodge, Gasser Auda, Mohamed Kamel:
Learning decision fusion in cooperative modular neural networks. 2777-2781 - Homayoun Navabi:
ARO network: a temporal fusion based neural architecture for low level vision. 2782-2787 - Mark W. Owen, Stephen C. Stubberud:
Interacting multiple model tracking using a neural extended Kalman filter. 2788-2791 - Erik Philip Blasch:
Biological information fusion using a PCNN and belief filtering. 2792-2795 - Raj P. Malhotra, Yan M. Yufik:
Graph-theoretic networks for holistic information fusion. 2796-2801
Character Recognition
- Ramaswamy Palaniappan, P. Raveendran, Sigeru Omatu:
Noise tolerant moments for neural network classification. 2802-2807 - Mingsheng Zhao, Youshou Wu:
Hybrid neural networks system for large scale Chinese character set recognition. 2808-2811 - Jorma Laaksonen, Matti Aksela, Erkki Oja, Jari Kangas:
Adaptive local subspace classifier in on-line recognition of handwritten characters. 2812-2815 - Khurshid Ahmad, Tracey A. Bale, Darren Burford:
Text classification and minimal-bias training vectors. 2816-2819 - Stéphane Lecoeuche, Jean-Paul Dubuso:
Introduction of a new notion into RBF networks: the shape concept. 2820-2823 - John C. M. Lee:
Automatic character recognition for moving and stationary vehicles and containers in real-life images. 2824-2828 - Shailesh Kumar, Melba M. Crawford, Joydeep Ghosh:
A versatile framework for labelling imagery with a large number of classes. 2829-2833 - Nayer M. Wanas, Mahmoud R. El-Sakka, Mohamed S. Kamel:
Multiple classifier hierarchical architecture for handwritten Arabic character recognition. 2834-2838 - Markus V. Lamari, Md. Shoaib Bhuiyan, Akira Iwata:
Hand alphabet recognition using morphological PCA and neural networks. 2839-2844 - Khue Hiang Chan, Sevki S. Erdogan:
Incremental learning for linear fusion of handwritten Chinese character classifiers. 2845-2849 - Neal F. Johnson:
The psychology of word recognition. 2850-2854
Word Recognition and Signature Verification
- Ernst M. Kussul, Lora M. Kasatkina:
Neural network system for continuous hand-written words recognition. 2855-2858 - Yong Liu, Bin Zhao, Shaowei Xia, Ming-Sheng Zhao:
A self-organizing network with fuzzy hyperellipsoidal classifying and its application in handwritten numeral recognition. 2859-2862 - Mingsheng Zhao, Youshou Wu:
TAF neural network for handwritten digits recognition. 2863-2866 - Seiichi Ozawa, Toshihide Tsujimoto, Manabu Kotani, Norio Baba:
Application of independent component analysis to handwritten Japanese character recognition. 2867-2871 - Jae-Hyun Cho, Chul-Woo Park, Eui-Young Cha:
Learning-data composition and recognition using fractal parameters. 2872-2875 - Qiuming Zhu, Luzheng Liu:
Building an accretive authentication system using a RBF network. 2876-2881 - Juliana Neiva de Gouvea Ribeiro, Germano Crispim Vasconcelos:
Off-line signature verification using an auto-associator cascade-correlation architecture. 2882-2886 - Khue Hiang Chan, Sevki S. Erdogan:
A new convolutional map feature extraction for character recognition. 2887-2892 - Michael Blumenstein, Brijesh K. Verma:
A new segmentation algorithm for handwritten word recognition. 2893-2898 - B. V. S. Murthy:
Handwriting recognition using supervised neural networks. 2899-2902 - Adnan Amin, Nabeel Murshed:
Recognition of printed Arabic words with fuzzy ARTMAP neural network. 2903-2907
Digit Recognition and Document Processing
- Mario I. Chacon Murguia, Jay B. Jordan:
Fuzzy neural network for document region classification using human visual perception features. 2908-2913 - Yong Liu, Song Wang, Yi-Long Liang, Shaowei Xia, Ming-Sheng Zhao:
Unconstrained handwritten numeral recognition with improved radial basis neural network. 2914-2919 - Han-Go Choi, Jae-Heung Cho, Sang-Hee Kim, Sang-Jae Lee:
Recognition of unconstrained handwritten digits using modified chaotic neural networks. 2920-2923 - Edmund S. Yu, Elizabeth D. Liddy:
Feature selection in text categorization using the Baldwin effect. 2924-2927 - Ajantha S. Atukorale, Ponnuthurai N. Suganthan:
Combining multiple HONG networks for recognizing unconstrained handwritten numerals. 2928-2933 - Jianchang Mao:
Neural networks in off-line text recognition: a review. 2934-2939
Speech Recognition
- Ke Chen, Huisheng Chi:
On use of different feature sets for pattern classification: an alternative method. 2940-2945 - Roberto Gemello, Dario Albesano, Franco Mana:
Multi-source neural networks for speech recognition. 2946-2949 - Chularat Tanprasert, Chai Wutiwiwatchai, Sutat Sae-Tang:
Text-dependent speaker identification using neural network on distinctive Thai tone marks. 2950-2953 - Lyne R. Palomar, Toshio Fukuda, Elmer P. Dadios:
A comparative analysis of the topological structures of different LPC feature-based speech models. 2954-2958 - Tong Zhao, Peng-Yung Woo:
Fuzzy speech recognition. 2959-2961 - Yong-Qian Ying, Peng-Yung Woo:
Speech recognition using fuzzy logic. 2962-2964 - Václav Sebesta, Jana Tucková:
Selection of important input parameters for a text-to-speech synthesis by neural networks. 2965-2969 - Qiong Liu, Sylvian R. Ray, Stephen E. Levinson, Thomas S. Huang, Jun Huang:
Temporal sequence learning and recognition with dynamic SOM. 2970-2975 - Darren K. Emge, Tülay Adali, M. Kemal Sönmez:
Least relative entropy for voiced/unvoiced speech classification. 2976-2980 - Manabu Kotani, Yasunobu Shirata, Satoshi Maekawa, Seiichi Ozawa, Kenzo Akazawa:
Application of independent component analysis to feature extraction of speech. 2981-2984 - Eun-Young Park, Sang-Hun Kim, Jae-Ho Chung:
Automatic speech synthesis unit generation with MLP based postprocessor against auto-segmented phoneme errors. 2985-2990 - Qing Ma, Kiyotaka Uchimoto, Masaki Murata, Hitoshi Isahara:
Elastic neural networks for part of speech tagging. 2991-2996 - Lin Zhong, Yuanyuan Shi, Runsheng Liu:
A dynamic neural network for syllable recognition. 2997-3001 - Nikola K. Kasabov:
Evolving connectionist systems: A theory and a case study on adaptive speech recognition. 3002-3007 - Younès Bennani:
Adaptive weighting of pattern features during learning. 3008-3013 - Ki-Young Park, Soo-Young Lee:
Selective attention for robust speech recognition in noisy environments. 3014-3019 - Dragan Jevtic:
How the internal state subnetwork works. 3020-3024 - Shajith Ikbal, Hemant Misra, B. Yegnanarayana:
Analysis of autoassociative mapping neural networks. 3025-3029 - Sihem Ben Sassi, Rafik Braham, Abdelfettah Belghith:
A text-to-speech system for Arabic using neural networks. 3030-3033 - Man-Wai Mak, C. K. Li:
Elliptical basis function networks and radial basis function networks for speaker verification: a comparative study. 3034-3039 - Patrizia Bonaventura, Marco Gori, Franco Scarselli, Pierluigi Salza, Jianqing Sheng:
A connectionist-based model for predicting the linguistic origin of surnames. 3040-3045 - Cyril Chavy, Bruno Gas, Jean-Luc Zarader:
Neural predictive coding applied to noisy phoneme recognition. 3046-3049 - Dan Ventura, D. Randall Wilson, Brian Moncur, Tony R. Martinez:
A neural model of centered tri-gram speech recognition. 3050-3053
Pattern Classifkation
- Koji Tsuda:
Subspace classifier in reproducing kernel Hilbert space. 3054-3057 - Chai-Lun J. Hu:
A novel, fast-learning, non-iterative neural network used in pattern recognition. 3058-3062 - Dong-Chul Park, Jio Jung, Seok-Yong Moon, Yong Cho:
A HMM training algorithm with query-based learning for refinement of classification boundary. 3063-3068 - Kagan Turner, Nikunj C. Oza:
Decimated input ensembles for improved generalization. 3069-3074 - Camillo Gentile, Mario Sznaier:
An improved Voronoi-diagram based neural net for pattern classification. 3075-3080 - Bao-Qing Li, Baoxin Li:
Building pattern classifiers using convolutional neural networks. 3081-3085 - Byungho Hwang, Sungzoon Cho:
Characteristics of auto-associative MLP as a novelty detector. 3086-3091 - Humberto Costa de Sousa, André C. P. L. F. de Carvalho:
Pattern recognition using constructive algorithms. 3092-3097 - R. J. Kuo, S. C. Chi, B. W. Den:
A fuzzy Kohonen's feature map neural network with application to group technology. 3098-3101 - Terry Windeatt:
Spectral partitioning for boundary estimation. 3102-3107 - Wlodzislaw Duch, Karol Grudzinski:
Search and global minimization in similarity-based methods. 3108-3113 - David McLean, Zuhair Bandar, James O'Shea:
Decision boundary modelling-a constructive algorithm for high precision real world data models. 3114-3118 - Thiagarajan Balachander, Ravi Kothari:
Kernel based subspace pattern classification. 3119-3122
Object and Target Recognition
- Gu Lin, Bingxue Shi:
A expansible current-mode sorting integrated circuit for pattern recognition. 3123-3127 - Michael A. Sipe, David P. Casasent:
Global feature space neural network for active object recognition. 3128-3133 - C. Yuan, Heinrich Niemann:
Object localization in 2D images based on Kohonen's self-organization feature maps. 3134-3137 - Sung Wook Baik, Peter Pachowicz:
Adaptive object recognition based on the radial basis function paradigm. 3138-3142 - Soonil D. Rughooputh, Harry C. S. Rughooputh:
Forensic application of a novel hybrid neural network. 3143-3146 - Christodoulos A. Nicolaou, Allan L. Egbert Jr., Robert Christopher Lacher, Susan I. Bassett:
Human shape recognition using the method of moments and artificial neural networks. 3147-3151 - Richard W. Ross, David L. Hibler:
Target recognition using neural networks for model deformation measurements. 3152-3155 - Giovanna Castellano, Anna Maria Fanelli:
Feature selection: a neural approach. 3156-3160 - LipChen Alex Chan, Nasser M. Nasrabadi, Don J. Torrieri:
Selectively optimized networks for automatic clutter rejection. 3161-3164 - Dean K. McNeill, Howard C. Card:
Competitive learning for extraction of visual representations of motion. 3165-3169 - Akihiro Watanabe, Michinori Andoh, Naoya Chujo, Yoshihisa Harata:
Neocognitron capable of position detection and vehicle recognition. 3170-3173 - Yanxin Zhang, Yue Liu, Zhuang Song:
Invariant image encoding in neural network for target recognition. 3174-3176 - Cheryl Resch, Fernando J. Pineda, I-Jeng Wang:
Automatic recognition and assignment of missile pieces in clutter. 3177-3181 - Moritoshi Yasunaga, Taro Nakamura, Ikuo Yoshihara:
Sonar spectrum recognition chip designed by evolutionary algorithm. 3182-3187 - Sameh M. Yamany, Ahmed M. El-Bialy, Aly A. Farag:
Object recognition using neural networks and surface signatures. 3188-3193 - Mu-Chun Su, Chien-Hsing Chou:
Application of associative memory in human face detection. 3194-3197 - Qun Zhao, José C. Príncipe:
Improving ATR performance by incorporating virtual negative examples. 3198-3203
Signal Recognition
- Julie A. Dickerson, J. Hong, Z. Cox, D. Bailey:
A comparison of radial basis function networks and fuzzy neural logic networks for autonomous star recognition. 3204-3207 - Ted Kerstetter, Stoney Massey, Joe Roberts:
Recursively partitioning neural networks for radar target recognition. 3208-3212 - Zhuoer Shi, Desheng Zhang, Donald J. Kouri, David K. Hoffman:
Robust regularized learning using distributed approximating functional networks. 3213-3216 - Xi Yu, Mahmood R. Azimi-Sadjadi:
A neural network-based sequential Bayes classifier for moving target discrimination. 3217-3220 - De Yao, Mahmood R. Azimi-Sadjadi, Gerald J. Dobeck:
Adaptive feature mapping for underwater target classification. 3221-3224 - Beatrice Lazzerini, Adriana Maggiore, Francesco Marcelloni:
A new linguistic fuzzy approach to recognition of olfactory signals. 3225-3229 - Gary G. Yen, Phayung Meesad:
Pattern classification by an incremental learning fuzzy neural network. 3230-3235 - Hossam Abdelbaki, Erol Gelenbe, Tashin Koçak:
Matched neural filters for EMI based mine detection. 3236-3240 - Hossam Abdelbaki, Erol Gelenbe, Said E. El-Khamy:
Random neural network decoder for error correcting codes. 3241-3245
Biometrics (Special Session)
- Fumiaki Takeda, Toshihiro Nishikage, Yoshiyuki Matsumoto:
Development of autonomic neural board for banknotes and advancement to palm prints recognition. 3246-3250 - Wenyi Feng, Yingbai Yan, Guofan Jin, Minxian Wu, Qingsheng He:
Neural network designed volume holographic wavelet correlator for pattern recognition. 3251-3254 - Vijay K. Sagar, Jit Beng Alex Koh:
Hybrid fuzzy logic and neural network model for fingerprint minutiae extraction. 3255-3259 - W. Zhao:
Subspace methods in object/face recognition. 3260-3264 - Karl Ricanek Jr., Gary L. Lebby, Kirk Haywood:
Hopfield like networks for pattern recognition with application to face recognition. 3265-3269 - Atsushi Mimura, Masafumi Hagiwata:
Understanding presumption system from facial images. 3270-3275 - Seok Won Lee, Boo Hee Nam:
Fingerprint recognition using wavelet transform and probabilistic neural network. 3276-3279 - Metin Artiklar, Mohamad H. Hassoun, Paul Watta:
Application of a post-processing algorithm for improved human face recognition. 3280-3283 - Anil K. Jain, Salil Prabhakar, Sharath Pankanti:
A filterbank-based representation for classification and matching of fingerprints. 3284-3285
Biometrics (Special Session
- Ashit Talukder, David P. Casasent:
Pose-invariant recognition of faces at unknown aspect views. 3286-3290 - Méziane Yacoub, Younès Bennani:
Discriminative feature extraction and selection applied to face recognition. 3291-3294 - Leenesh Kumar Maisuria, Cheng Soon Ong, Wen Kin Lai:
A comparison of artificial neural networks and cluster analysis for typing biometrics authentication. 3295-3299