Google
Google Scholar
MS Academic
CiteSeerX
CORE
Semantic ScholarNikola K. Kasabov
Nikola Kasabov
Person information
- affiliation: Auckland University of Technology, Knowledge Engineering & Discovery Research Institute (KEDRI)
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
showing all ?? records
2010 – today
- 2018
[j128]Xiaohui Huang, Zhenhong Jia, Junlin Zhou, Jie Yang, Nikola Kasabov:
Speckle Reduction of Reconstructions of Digital Holograms Using Gamma-Correction and Filtering. IEEE Access 6: 5227-5235 (2018)- [j127]Obada Al Zoubi, Mariette Awad, Nikola K. Kasabov:
Anytime multipurpose emotion recognition from EEG data using a Liquid State Machine based framework. Artificial Intelligence in Medicine 86: 1-8 (2018) - [j126]Zohreh Gholami Doborjeh, Maryam Gholami Doborjeh, Nikola Kasabov:
Attentional Bias Pattern Recognition in Spiking Neural Networks from Spatio-Temporal EEG Data. Cognitive Computation 10(1): 35-48 (2018) - [j125]Fahad Bashir Alvi, Russel Pears, Nikola Kasabov:
An evolving spatio-temporal approach for gender and age group classification with Spiking Neural Networks. Evolving Systems 9(2): 145-156 (2018) - [j124]Maryam Gholami Doborjeh, Nikola Kasabov, Zohreh Gholami Doborjeh:
Evolving, dynamic clustering of spatio/spectro-temporal data in 3D spiking neural network models and a case study on EEG data. Evolving Systems 9(3): 195-211 (2018) - [j123]Lukas Paulun, Anne Wendt, Nikola Kasabov:
A Retinotopic Spiking Neural Network System for Accurate Recognition of Moving Objects Using NeuCube and Dynamic Vision Sensors. Front. Comput. Neurosci. 2018 (2018) - [j122]Jesus L. Lobo, Ibai Laña, Javier Del Ser, Miren Nekane Bilbao, Nikola Kasabov:
Evolving Spiking Neural Networks for online learning over drifting data streams. Neural Networks 108: 1-19 (2018) - [j121]Cheng Peng, Fanghui Liu, Jie Yang, Nikola Kasabov:
Densely Connected Discriminative Correlation Filters for Visual Tracking. IEEE Signal Process. Lett. 25(7): 1019-1023 (2018) - [j120]Cheng Peng, Fanghui Liu, Jie Yang, Nikola Kasabov:
Robust Visual Tracking via Dirac-Weighted Cascading Correlation Filters. IEEE Signal Process. Lett. 25(11): 1700-1704 (2018) - [j119]Neelava Sengupta, Carolyn B. McNabb, Nikola Kasabov, Bruce Russell:
Integrating Space, Time, and Orientation in Spiking Neural Networks: A Case Study on Multimodal Brain Data Modeling. IEEE Trans. Neural Netw. Learning Syst. 29(11): 5249-5263 (2018) - [c142]Lu Wang, Chao Ma, Enmei Tu, Jie Yang, Nikola Kasabov:
Discrete Sparse Hashing for Cross-Modal Similarity Search. ICONIP (4) 2018: 256-267 - [c141]Mingjian Chen, Hao Zheng, Changsheng Lu, Enmei Tu, Jie Yang, Nikola Kasabov:
A Spatio-Temporal Fully Convolutional Network for Breast Lesion Segmentation in DCE-MRI. ICONIP (7) 2018: 358-368 - [c140]Gautam Kishore Shahi, Imanol Bilbao, Elisa Capecci, Durgesh Nandini, Maria Choukri, Nikola Kasabov:
Analysis, Classification and Marker Discovery of Gene Expression Data with Evolving Spiking Neural Networks. ICONIP (5) 2018: 517-527 - [c139]Durgesh Nandini, Elisa Capecci, Lucien Koefoed, Ibai Laña, Gautam Kishore Shahi, Nikola Kasabov:
Modelling and Analysis of Temporal Gene Expression Data Using Spiking Neural Networks. ICONIP (1) 2018: 571-581 - [c138]Jack Dray, Elisa Capecci, Nikola Kasabov:
Spiking Neural Networks for Cancer Gene Expression Time Series Modelling and Analysis. ICONIP (1) 2018: 625-634 - [c137]Kaushalya Kumarasinghe, Mahonri Owen, Denise Taylor, Nikola Kasabov, Chi Kit:
FaNeuRobot: A Framework for Robot and Prosthetics Control Using the NeuCube Spiking Neural Network Architecture and Finite Automata Theory. ICRA 2018: 1-8 - [c136]Jesus L. Lobo, Javier Del Ser, Ibai Laña, Miren Nekane Bilbao, Nikola Kasabov:
Drift Detection over Non-stationary Data Streams Using Evolving Spiking Neural Networks. IDC 2018: 82-94 - [c135]Ibai Laña, Elisa Capecci, Javier Del Ser, Jesus L. Lobo, Nikola Kasabov:
Road Traffic Forecasting Using NeuCube and Dynamic Evolving Spiking Neural Networks. IDC 2018: 192-203 - [c134]Zohreh Gholami Doborjeh, Maryam Gholami Doborjeh, Nikola Kasabov:
EEG Pattern Recognition using Brain-Inspired Spiking Neural Networks for Modelling Human Decision Processes. IJCNN 2018: 1-7 - [c133]Lucien Koefoed, Elisa Capecci, Nikola Kasabov:
Analysis of Gene Expression Time Series Data of Ebola Vaccine response using the NeuCube and Temporal Feature Selection. IJCNN 2018: 1-7 - 2017
- [j118]Dayong Ren, Zhenhong Jia, Jie Yang, Nikola K. Kasabov:
A Practical GrabCut Color Image Segmentation Based on Bayes Classification and Simple Linear Iterative Clustering. IEEE Access 5: 18480-18487 (2017) - [j117]Chenjie Ge, Nikola Kasabov, Zhi Liu, Jie Yang:
A spiking neural network model for obstacle avoidance in simulated prosthetic vision. Inf. Sci. 399: 30-42 (2017) - [j116]Neelava Sengupta, Nikola Kasabov:
Spike-time encoding as a data compression technique for pattern recognition of temporal data. Inf. Sci. 406: 133-145 (2017) - [j115]Pengyun Chen, Yichen Zhang, Zhenhong Jia, Jie Yang, Nikola Kasabov:
Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application. Sensors 17(6): 1295 (2017) - [j114]Zhiqing Guo, Zhenhong Jia, Jie Yang, Nikola Kasabov, Chuanxi Li:
Image Processing of Porous Silicon Microarray in Refractive Index Change Detection. Sensors 17(6): 1335 (2017) - [j113]Nikola Kasabov, Lei Zhou, Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh, Jie Yang:
New Algorithms for Encoding, Learning and Classification of fMRI Data in a Spiking Neural Network Architecture: A Case on Modeling and Understanding of Dynamic Cognitive Processes. IEEE Trans. Cognitive and Developmental Systems 9(4): 293-303 (2017) - [j112]Nikola K. Kasabov, Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh:
Mapping, Learning, Visualization, Classification, and Understanding of fMRI Data in the NeuCube Evolving Spatiotemporal Data Machine of Spiking Neural Networks. IEEE Trans. Neural Netw. Learning Syst. 28(4): 887-899 (2017) - [j111]Enmei Tu, Nikola Kasabov, Jie Yang:
Mapping Temporal Variables Into the NeuCube for Improved Pattern Recognition, Predictive Modeling, and Understanding of Stream Data. IEEE Trans. Neural Netw. Learning Syst. 28(6): 1305-1317 (2017) - [c132]Cheng Peng, Fanghui Liu, Haiyan Yang, Jie Yang, Nikola Kasabov:
Correlation Filters with Adaptive Memories and Fusion for Visual Tracking. ICONIP (3) 2017: 170-179 - [c131]Fanghui Liu, Xiaolin Huang, Cheng Peng, Jie Yang, Nikola Kasabov:
Robust Kernel Approximation for Classification. ICONIP (1) 2017: 289-296 - [c130]Yuma Omori, Hideaki Kawano, Akinori Seo, Zohreh Gholami Doborjeh, Nikola Kasabov, Maryam Gholami Doborjeh:
EEG Comparison Between Normal and Developmental Disorder in Perception and Imitation of Facial Expressions with the NeuCube. ICONIP (4) 2017: 596-601 - 2016
- [j110]Tao Gao, Nikola Kasabov:
Adaptive cow movement detection using evolving spiking neural network models. Evolving Systems 7(4): 277-285 (2016) - [j109]Yu Cheng, Zhigang Jin, Tao Gao, Hongcai Chen, Nikola Kasabov:
An improved collaborative representation based classification with regularized least square (CRC-RLS) method for robust face recognition. Neurocomputing 215: 250-259 (2016) - [j108]Enmei Tu, Yaqian Zhang, Lin Zhu, Jie Yang, Nikola Kasabov:
A graph-based semi-supervised k nearest-neighbor method for nonlinear manifold distributed data classification. Inf. Sci. 367-368: 673-688 (2016) - [j107]Nikola Kasabov, Nathan Matthew Scott, Enmei Tu, Stefan Marks, Neelava Sengupta, Elisa Capecci, Muhaini Othman, Maryam Gholami Doborjeh, Norhanifah Murli, Reggio N. Hartono, Josafath Israel Espinosa Ramos, Lei Zhou, Fahad Bashir Alvi, Grace Y. Wang, Denise Taylor, Valery Feigin, Sergei Gulyaev, Mahmoud S. Mahmoud, Zeng-Guang Hou, Jie Yang:
Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications. Neural Networks 78: 1-14 (2016) - [j106]Maryam Gholami Doborjeh, Grace Y. Wang, Nikola K. Kasabov, Robert Kydd, Bruce Russell:
A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects. IEEE Trans. Biomed. Engineering 63(9): 1830-1841 (2016) - [j105]Hao Wu, Lin Gao, Nikola K. Kasabov:
Network-Based Method for Inferring Cancer Progression at the Pathway Level from Cross-Sectional Mutation Data. IEEE/ACM Trans. Comput. Biology Bioinform. 13(6): 1036-1044 (2016) - [j104]Pritam Bose, Nikola K. Kasabov, Lorenzo Bruzzone, Reggio N. Hartono:
Spiking Neural Networks for Crop Yield Estimation Based on Spatiotemporal Analysis of Image Time Series. IEEE Trans. Geoscience and Remote Sensing 54(11): 6563-6573 (2016) - [c129]Vivienne Breen, Nikola Kasabov, Peng Du, Stefan Calder:
A Spiking Neural Network for Personalised Modelling of Electrogastrography (EGG). ANNPR 2016: 18-25 - [c128]Hideaki Kawano, Akinori Seo, Zohreh Gholami Doborjeh, Nikola K. Kasabov, Maryam Gholami Doborjeh:
Analysis of Similarity and Differences in Brain Activities Between Perception and Production of Facial Expressions Using EEG Data and the NeuCube Spiking Neural Network Architecture. ICONIP (4) 2016: 221-227 - [c127]Zohreh Gholami Doborjeh, Maryam Gholami Doborjeh, Nikola Kasabov:
Efficient Recognition of Attentional Bias Using EEG Data and the NeuCube Evolving Spatio-Temporal Data Machine. ICONIP (4) 2016: 645-653 - [c126]Elisa Capecci, Zohreh Gholami Doborjeh, Nadia Mammone, Fabio La Foresta, Francesco Carlo Morabito, Nikola Kasabov:
Longitudinal study of alzheimer's disease degeneration through EEG data analysis with a NeuCube spiking neural network model. IJCNN 2016: 1360-1366 - [c125]Anne Abbott, Neelava Sengupta, Nikola Kasabov:
Which method to use for optimal structure and function representation of large spiking neural networks: A case study on the NeuCube architecture. IJCNN 2016: 1367-1372 - [c124]Maryam Gholami Doborjeh, Nikola Kasabov:
Personalised modelling on integrated clinical and EEG Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network system. IJCNN 2016: 1373-1378 - [c123]Nikola Kasabov, Neelava Sengupta, Nathan Matthew Scott:
From von neumann, John Atanasoff and ABC to Neuromorphic computation and the NeuCube spatio-temporal data machine. IEEE Conf. on Intelligent Systems 2016: 15-21 - [i2]Enmei Tu, Nikola K. Kasabov, Jie Yang:
Mapping Temporal Variables into the NeuCube for Improved Pattern Recognition, Predictive Modelling and Understanding of Stream Data. CoRR abs/1603.05594 (2016) - [i1]Enmei Tu, Yaqian Zhang, Lin Zhu, Jie Yang, Nikola K. Kasabov:
A Graph-Based Semi-Supervised k Nearest-Neighbor Method for Nonlinear Manifold Distributed Data Classification. CoRR abs/1606.00985 (2016) - 2015
- [j103]Hao Wu, Lin Gao, Feng Li, Fei Song, Xiaofei Yang, Nikola Kasabov:
Identifying overlapping mutated driver pathways by constructing gene networks in cancer. BMC Bioinformatics 16(S-5): S3 (2015) - [j102]Wen Liang, Yingjie Hu, Nikola K. Kasabov:
Evolving personalized modeling system for integrated feature, neighborhood and parameter optimization utilizing gravitational search algorithm. Evolving Systems 6(1): 1-14 (2015) - [j101]Enmei Tu, Jie Yang, Nikola Kasabov, Yaqian Zhang:
Posterior Distribution Learning (PDL): A novel supervised learning framework using unlabeled samples to improve classification performance. Neurocomputing 157: 173-186 (2015) - [j100]Jing-jing Wang, Zhenhong Jia, Xizhong Qin, Jie Yang, Nikola K. Kasabov:
Medical image enhancement algorithm based on NSCT and the improved fuzzy contrast. Int. J. Imaging Systems and Technology 25(1): 7-14 (2015) - [j99]Lu Liu, Zhenhong Jia, Jie Yang, Nikola Kasabov:
A medical image enhancement method using adaptive thresholding in NSCT domain combined unsharp masking. Int. J. Imaging Systems and Technology 25(3): 199-205 (2015) - [j98]Nikola Kasabov, Elisa Capecci:
Spiking neural network methodology for modelling, classification and understanding of EEG spatio-temporal data measuring cognitive processes. Inf. Sci. 294: 565-575 (2015) - [j97]Tao Gao, Nikola Kasabov:
A method used for Dotted Data Matrix image processing. J. Comput. Meth. in Science and Engineering 15(4): 685-693 (2015) - [j96]Nikola K. Kasabov:
Evolving connectionist systems for adaptive learning and knowledge discovery: Trends and directions. Knowl.-Based Syst. 80: 24-33 (2015) - [j95]Elisa Capecci, Nikola Kasabov, Grace Y. Wang:
Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment. Neural Networks 68: 62-77 (2015) - [c122]Maryam Gholami Doborjeh, Nikola K. Kasabov:
Dynamic 3D Clustering of Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network Architecture on a Case Study of fMRI Data. ICONIP (4) 2015: 191-198 - [c121]Yu Zhao, Yu Qiao, Jie Yang, Nikola Kasabov:
Abnormal Activity Detection Using Spatio-Temporal Feature and Laplacian Sparse Representation. ICONIP (4) 2015: 410-418 - [c120]Shaoyong Jia, Yuding Liang, Xianyang Chen, Yun Gu, Jie Yang, Nikola K. Kasabov, Yu Qiao:
Adaptive Location for Multiple Salient Objects Detection. ICONIP (3) 2015: 411-418 - [c119]Liangdong Li, Nikola Kasabov, Jie Yang, Lixiu Yao, Zhenghong Jia:
Poisson Image Denoising Based on BLS-GSM Method. ICONIP (4) 2015: 513-522 - [c118]Elisa Capecci, Josafath Israel Espinosa Ramos, Nadia Mammone, Nikola K. Kasabov, Jonas Duun-Henriksen, Troels Wesenberg Kjaer, Maurizio Campolo, Fabio La Foresta, Francesco Carlo Morabito:
Modelling Absence Epilepsy seizure data in the NeuCube evolving spiking neural network architecture. IJCNN 2015: 1-8 - [c117]Long Peng, Zeng-Guang Hou, Nikola Kasabov, Jin Hu, Liang Peng, Weiqun Wang:
sEMG-based torque estimation for robot-assisted lower limb rehabilitation. IJCNN 2015: 1-5 - [p8]Nikola Kasabov:
Evolving Connectionist Systems: From Neuro-Fuzzy-, to Spiking- and Neuro-Genetic. Handbook of Computational Intelligence 2015: 771-782 - [e9]Plamen P. Angelov, Krassimir T. Atanassov, Lyubka Doukovska, Mincho Hadjiski, Vladimir Simov Jotsov, Janusz Kacprzyk, Nikola Kasabov, Sotir Sotirov, Eulalia Szmidt, Slawomir Zadrozny:
Intelligent Systems'2014 - Proceedings of the 7th International Conference Intelligent Systems IEEE IS'2014, September 24-26, 2014, Warsaw, Poland, Volume 1: Mathematical Foundations, Theory, Analyses. Advances in Intelligent Systems and Computing 322, Springer 2015, ISBN 978-3-319-11312-8 [contents] - 2014
- [j94]Xin Yi, Yingjie Hu, Zhenhong Jia, Liejun Wang, Jie Yang, Nikola K. Kasabov:
An enhanced multiphase Chan-Vese model for the remote sensing image segmentation. Concurrency and Computation: Practice and Experience 26(18): 2893-2906 (2014) - [j93]Nikola Kasabov, Valery Feigin, Zeng-Guang Hou, Yixiong Chen, Linda Liang, Rita Krishnamurthi, Muhaini Othman, Priya Parmar:
Evolving spiking neural networks for personalised modelling, classification and prediction of spatio-temporal patterns with a case study on stroke. Neurocomputing 134: 269-279 (2014) - [j92]Enmei Tu, Longbing Cao, Jie Yang, Nikola Kasabov:
A novel graph-based k-means for nonlinear manifold clustering and representative selection. Neurocomputing 143: 109-122 (2014) - [j91]Nikola K. Kasabov:
NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data. Neural Networks 52: 62-76 (2014) - [c116]Jin Hu, Zeng-Guang Hou, Yixiong Chen, Nikola Kasabov, Nathan Matthew Scott:
EEG-based classification of upper-limb ADL using SNN for active robotic rehabilitation. BioRob 2014: 409-414 - [c115]Maryam Gholami Doborjeh, Elisa Capecci, Nikola Kasabov:
Classification and segmentation of fMRI Spatio-Temporal Brain Data with a NeuCube evolving Spiking Neural Network model. EALS 2014: 73-80 - [c114]Wei Zhang, Jie Yang, Wenjing Jia, Nikola Kasabov, Zhenhong Jia, Lei Zhou:
Unsupervised Segmentation Using Cluster Ensembles. ICONIP (3) 2014: 76-84 - [c113]Enmei Tu, Jie Yang, Zhenghong Jia, Nikola Kasabov:
Posterior Distribution Learning (PDL): A Novel Supervised Learning Framework. ICONIP (1) 2014: 86-94 - [c112]Norhanifah Murli, Nikola Kasabov, Bana Handaga:
Classification of fMRI Data in the NeuCube Evolving Spiking Neural Network Architecture. ICONIP (1) 2014: 421-428 - [c111]Enmei Tu, Nikola K. Kasabov, Muhaini Othman, Yuxiao Li, Susan P. Worner, Jie Yang, Zhenghong Jia:
NeuCube(ST) for spatio-temporal data predictive modelling with a case study on ecological data. IJCNN 2014: 638-645 - [c110]Muhaini Othman, Nikola K. Kasabov, Enmei Tu, Valery Feigin, Rita Krishnamurthi, Zhengguang Hou, Yixiong Chen, Jin Hu:
Improved predictive personalized modelling with the use of Spiking Neural Network system and a case study on stroke occurrences data. IJCNN 2014: 3197-3204 - [c109]Denise Taylor, Nathan Matthew Scott, Nikola K. Kasabov, Elisa Capecci, Enmei Tu, Nicola Saywell, Yixiong Chen, Jin Hu, Zeng-Guang Hou:
Feasibility of NeuCube SNN architecture for detecting motor execution and motor intention for use in BCIapplications. IJCNN 2014: 3221-3225 - [c108]Reggio N. Hartono, Russel Pears, Nikola K. Kasabov, Susan P. Worner:
Extracting temporal knowledge from time series: A case study in ecological data. IJCNN 2014: 4237-4243 - 2013
- [j90]Stefan Schliebs, Nikola Kasabov:
Evolving spiking neural network - a survey. Evolving Systems 4(2): 87-98 (2013) - [j89]Russel Pears, Harya Widiputra, Nikola Kasabov:
Evolving integrated multi-model framework for on line multiple time series prediction. Evolving Systems 4(2): 99-117 (2013) - [j88]Ammar Mohemmed, Stefan Schliebs, Satoshi Matsuda, Nikola Kasabov:
Training spiking neural networks to associate spatio-temporal input-output spike patterns. Neurocomputing 107: 3-10 (2013) - [j87]Ivan Jordanov, Bruno Apolloni, Nikola Kasabov:
Special Issue: Contemporary development of neural computation and applications. Neural Computing and Applications 22(1): 1-2 (2013) - [c107]Stefan Schliebs, Nikola Kasabov, Dave Parry, Doug Hunt:
Towards a Wearable Coach: Classifying Sports Activities with Reservoir Computing. EANN (1) 2013: 233-242 - [c106]Stefan Schliebs, Elisa Capecci, Nikola Kasabov:
Spiking Neural Network for On-line Cognitive Activity Classification Based on EEG Data. ICONIP (3) 2013: 55-62 - [c105]Nikola Kasabov, Jin Hu, Yixiong Chen, Nathan Matthew Scott, Yulia Turkova:
Spatio-temporal EEG Data Classification in the NeuCube 3D SNN Environment: Methodology and Examples. ICONIP (3) 2013: 63-69 - [c104]Yixiong Chen, Jin Hu, Nikola Kasabov, Zeng-Guang Hou, Long Cheng:
NeuCubeRehab: A Pilot Study for EEG Classification in Rehabilitation Practice Based on Spiking Neural Networks. ICONIP (3) 2013: 70-77 - [c103]Nathan Matthew Scott, Nikola Kasabov, Giacomo Indiveri:
NeuCube Neuromorphic Framework for Spatio-temporal Brain Data and Its Python Implementation. ICONIP (3) 2013: 78-84 - [c102]
- [e8]Valeri Mladenov, Petia D. Koprinkova-Hristova, Günther Palm, Alessandro E. P. Villa, Bruno Appollini, Nikola Kasabov:
Artificial Neural Networks and Machine Learning - ICANN 2013 - 23rd International Conference on Artificial Neural Networks, Sofia, Bulgaria, September 10-13, 2013. Proceedings. Lecture Notes in Computer Science 8131, Springer 2013, ISBN 978-3-642-40727-7 [contents] - 2012
- [j86]Ammar Mohemmed, Stefan Schliebs, Satoshi Matsuda, Nikola Kasabov:
Span: Spike Pattern Association Neuron for Learning Spatio-Temporal Spike Patterns. Int. J. Neural Syst. 22(4) (2012) - [j85]Shaoning Pang, Tao Ban, Youki Kadobayashi, Nikola K. Kasabov:
LDA Merging and Splitting With Applications to Multiagent Cooperative Learning and System Alteration. IEEE Trans. Systems, Man, and Cybernetics, Part B 42(2): 552-564 (2012) - [c101]Nikola Kasabov:
NeuCube EvoSpike Architecture for Spatio-temporal Modelling and Pattern Recognition of Brain Signals. ANNPR 2012: 225-243 - [c100]Stefan Schliebs, Maurizio Fiasché, Nikola Kasabov:
Constructing Robust Liquid State Machines to Process Highly Variable Data Streams. ICANN (1) 2012: 604-611 - [c99]Ammar Mohemmed, Guoyu Lu, Nikola Kasabov:
Evaluating SPAN Incremental Learning for Handwritten Digit Recognition. ICONIP (3) 2012: 670-677 - [c98]Kshitij Dhoble, Nuttapod Nuntalid, Giacomo Indiveri, Nikola Kasabov:
Online spatio-temporal pattern recognition with evolving spiking neural networks utilising address event representation, rank order, and temporal spike learning. IJCNN 2012: 1-7 - [c97]Ammar Mohemmed, Nikola Kasabov:
Incremental learning algorithm for spatio-temporal spike pattern classification. IJCNN 2012: 1-6 - [c96]Nikola Kasabov:
Evolving spiking neural networks for spatio-and spectro-temporal pattern recognition. IEEE Conf. of Intelligent Systems 2012: 27-32 - [c95]Nikola Kasabov:
Evolving Spiking Neural Networks and Neurogenetic Systems for Spatio- and Spectro-Temporal Data Modelling and Pattern Recognition. WCCI 2012: 234-260 - [e7]Plamen P. Angelov, Dimitar P. Filev, Nikola Kasabov, José Antonio Iglesias, Germán Gutiérrez:
2012 IEEE Conference on Evolving and Adaptive Intelligent Systems, EAIS 2012, Madrid, Spain, May 17-18, 2012. IEEE 2012, ISBN 978-1-4673-1727-6 [contents] - 2011
- [j84]Harya Widiputra, Russel Pears, Nikola Kasabov:
Dynamic Interaction Networks versus Local Trend Models for Multiple Time-Series Prediction. Cybernetics and Systems 42(2): 100-123 (2011) - [j83]Shaoning Pang, Tao Ban, Youki Kadobayashi, Nikola Kasabov:
Personalized mode transductive spanning SVM classification tree. Inf. Sci. 181(11): 2071-2085 (2011) - [j82]Shaoning Pang, Lei Song, Nikola K. Kasabov:
Correlation-aided support vector regression for forex time series prediction. Neural Computing and Applications 20(8): 1193-1203 (2011) - [j81]Yaochu Jin, Yan Meng, Juyang Weng, Nikola Kasabov:
Guest Editorial Special Issue on Computational Modeling of Neural and Brain Development. IEEE Trans. Autonomous Mental Development 3(4): 273-275 (2011) - [j80]Nikola Kasabov, Reinhard Schliebs, Hiroshi Kojima:
Probabilistic Computational Neurogenetic Modeling: From Cognitive Systems to Alzheimer's Disease. IEEE Trans. Autonomous Mental Development 3(4): 300-311 (2011) - [c94]Nikola K. Kasabov, Stefan Schliebs, Ammar Mohemmed:
Modelling the Effect of Genes on the Dynamics of Probabilistic Spiking Neural Networks for Computational Neurogenetic Modelling. CIBB 2011: 1-9 - [c93]Wen Liang, Yingjie Hu, Nikola Kasabov, Valery Feigin:
Exploring Associations between Changes in Ambient Temperature and Stroke Occurrence: Comparative Analysis Using Global and Personalised Modelling Approaches. ICONIP (1) 2011: 129-137 - [c92]Stefan Schliebs, Haza Nuzly Abdull Hamed, Nikola Kasabov:
Reservoir-Based Evolving Spiking Neural Network for Spatio-temporal Pattern Recognition. ICONIP (2) 2011: 160-168 - [c91]Nikola Kasabov, Kshitij Dhoble, Nuttapod Nuntalid, Ammar Mohemmed:
Evolving Probabilistic Spiking Neural Networks for Spatio-temporal Pattern Recognition: A Preliminary Study on Moving Object Recognition. ICONIP (3) 2011: 230-239 - [c90]Nuttapod Nuntalid, Kshitij Dhoble, Nikola Kasabov:
EEG Classification with BSA Spike Encoding Algorithm and Evolving Probabilistic Spiking Neural Network. ICONIP (1) 2011: 451-460 - [c89]Yingjie Hu, Nikola Kasabov:
Personalised Modelling on SNPs Data for Crohn's Disease Prediction. ICONIP (1) 2011: 646-653 - [c88]Ammar Mohemmed, Stefan Schliebs, Nikola Kasabov:
SPAN: A Neuron for Precise-Time Spike Pattern Association. ICONIP (2) 2011: 718-725 - [c87]Ammar Mohemmed, Stefan Schliebs, Satoshi Matsuda, Nikola Kasabov:
Method for Training a Spiking Neuron to Associate Input-Output Spike Trains. EANN/AIAI (1) 2011: 219-228 - [c86]Haza Nuzly Abdull Hamed, Nikola Kasabov, Siti Mariyam Shamsuddin, Harya Widiputra, Kshitij Dhoble:
An extended Evolving Spiking Neural Network model for spatio-temporal pattern classification. IJCNN 2011: 2653-2656 - [c85]Ammar Mohemmed, Satoshi Matsuda, Stefan Schliebs, Kshitij Dhoble, Nikola Kasabov:
Optimization of Spiking Neural Networks with dynamic synapses for spike sequence generation using PSO. IJCNN 2011: 2969-2974 - [c84]Stefan Schliebs, Ammar Mohemmed, Nikola Kasabov:
Are probabilistic spiking neural networks suitable for reservoir computing? IJCNN 2011: 3156-3163 - [c83]Harya Widiputra, Russel Pears, Nikola Kasabov:
Multiple Time-Series Prediction through Multiple Time-Series Relationships Profiling and Clustered Recurring Trends. PAKDD (2) 2011: 161-172 - 2010
- [j79]Haza Nuzly Abdull Hamed, Nikola Kasabov, Siti Mariyam Shamsuddin:
Probabilistic Evolving Spiking Neural Network Optimization Using Dynamic Quantum-inspired Particle Swarm Optimization. Austr. J. Intelligent Information Processing Systems 11(1) (2010) - [j78]