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Mahdi Shaghaghi
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Journal Articles
- 2017
- [j3]Mahdi Shaghaghi, Raviraj S. Adve, George Shehata:
Training-Based Adaptive Transmit-Receive Beamforming for MIMO Radars. IEEE Trans. Aerosp. Electron. Syst. 53(6): 2899-2912 (2017) - 2015
- [j2]Mahdi Shaghaghi, Sergiy A. Vorobyov:
Cramér-Rao Bound for Sparse Signals Fitting the Low-Rank Model with Small Number of Parameters. IEEE Signal Process. Lett. 22(9): 1497-1501 (2015) - [j1]Mahdi Shaghaghi, Sergiy A. Vorobyov:
Subspace Leakage Analysis and Improved DOA Estimation With Small Sample Size. IEEE Trans. Signal Process. 63(12): 3251-3265 (2015)
Conference and Workshop Papers
- 2019
- [c6]Mahdi Shaghaghi, Raviraj S. Adve, Zhen Ding:
Resource Management for Multifunction Multichannel Cognitive Radars. ACSSC 2019: 1550-1554 - [c5]Mohamed Gaafar, Mahdi Shaghaghi, Raviraj S. Adve, Zhen Ding:
Reinforcement Learning for Cognitive Radar Task Scheduling. ACSSC 2019: 1653-1657 - 2015
- [c4]Mahdi Shaghaghi, Sergiy A. Vorobyov:
Subspace leakage analysis of sample data covariance matrix. ICASSP 2015: 3447-3451 - 2013
- [c3]Mahdi Shaghaghi, Sergiy A. Vorobyov:
Iterative root-MUSIC algorithm for DOA estimation. CAMSAP 2013: 53-56 - 2012
- [c2]Mahdi Shaghaghi, Sergiy A. Vorobyov:
Correlogram for undersampled data: Bias and variance analysis. ICASSP 2012: 3513-3516 - 2011
- [c1]Mahdi Shaghaghi, Sergiy A. Vorobyov:
Improved model-based spectral compressive sensing via nested least squares. ICASSP 2011: 3904-3907
Informal and Other Publications
- 2018
- [i4]Mahdi Shaghaghi, Raviraj S. Adve, Zhen Ding:
Multifunction Cognitive Radar Task Scheduling Using Monte Carlo Tree Search and Policy Networks. CoRR abs/1805.07069 (2018) - 2015
- [i3]Mahdi Shaghaghi, Sergiy A. Vorobyov:
Subspace Leakage Analysis and Improved DOA Estimation with Small Sample Size. CoRR abs/1502.00139 (2015) - [i2]Mahdi Shaghaghi, Sergiy A. Vorobyov:
Cramer-Rao Bound for Sparse Signals Fitting the Low-Rank Model with Small Number of Parameters. CoRR abs/1502.07523 (2015) - 2013
- [i1]Mahdi Shaghaghi, Sergiy A. Vorobyov:
Finite-Length and Asymptotic Analysis of Correlogram for Undersampled Data. CoRR abs/1305.5592 (2013)
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