2023 - Research.com Computer Science in Germany Leader Award
His primary areas of study are Algorithm, Mathematical optimization, Estimator, Robustness and Beamforming. His Algorithm study combines topics in areas such as Statistics, Sensor array and Direction of arrival. The concepts of his Mathematical optimization study are interwoven with issues in Matrix decomposition, Stochastic process and Convex optimization.
His research in Estimator intersects with topics in Calibration and Array processing. His studies deal with areas such as Telecommunications link and Adaptive beamformer as well as Robustness. His Adaptive beamformer research includes themes of Minimum-variance unbiased estimator, Second-order cone programming and Control theory.
Algorithm, Mathematical optimization, Robustness, Electronic engineering and Estimator are his primary areas of study. The various areas that Alex B. Gershman examines in his Algorithm study include Direction of arrival and Communication channel. His Mathematical optimization study integrates concerns from other disciplines, such as Computational complexity theory, Covariance, Polynomial and Convex optimization.
His research integrates issues of Multiuser detection, Second-order cone programming and Adaptive beamformer in his study of Robustness. His Adaptive beamformer research also works with subjects such as
Alex B. Gershman mainly investigates Beamforming, Relay, Algorithm, Electronic engineering and Communication channel. His Beamforming research integrates issues from Signal-to-noise ratio and Quality of service. His Algorithm research is multidisciplinary, relying on both MIMO, Estimator and Direction of arrival.
His work is dedicated to discovering how Communication channel, Control theory are connected with Estimation theory and other disciplines. The study incorporates disciplines such as Covariance and Mathematical optimization in addition to Covariance matrix. His Mathematical optimization research is multidisciplinary, incorporating perspectives in Adaptive beamformer, Robustness and Convex optimization.
His scientific interests lie mostly in Mathematical optimization, Beamforming, Algorithm, Communication channel and Robustness. His study in Mathematical optimization is interdisciplinary in nature, drawing from both Cognitive radio and Convex optimization. Alex B. Gershman has included themes like Relay and Computer network in his Beamforming study.
His Algorithm study combines topics from a wide range of disciplines, such as Sensor array, Direction of arrival and Semidefinite programming. His Communication channel research is multidisciplinary, incorporating perspectives in Transmitter and Control theory. His studies deal with areas such as Covariance matrix, Signal processing, Optimization problem, Telecommunications link and Adaptive beamformer as well as Robustness.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem
S.A. Vorobyov;A.B. Gershman;Zhi-Quan Luo.
IEEE Transactions on Signal Processing (2003)
Training-based MIMO channel estimation: a study of estimator tradeoffs and optimal training signals
M. Biguesh;A.B. Gershman.
IEEE Transactions on Signal Processing (2006)
Convex Optimization-Based Beamforming
Alex B Gershman;Nicholas D Sidiropoulos;Shahram Shahbazpanahi;Mats Bengtsson.
IEEE Signal Processing Magazine (2010)
Robust adaptive beamforming for general-rank signal models
S. Shahbazpanahi;A.B. Gershman;Zhi-Quan Luo;Kon Max Wong.
IEEE Transactions on Signal Processing (2003)
Fast antenna subset selection in MIMO systems
M. Gharavi-Alkhansari;A.B. Gershman.
IEEE Transactions on Signal Processing (2004)
Space-time processing for MIMO communications
Alex B Gershman;Alex B Gershman;Nikos Sidiropoulos.
The stochastic CRB for array processing: a textbook derivation
P. Stoica;E.G. Larsson;A.B. Gershman.
IEEE Signal Processing Letters (2001)
Unitary root-MUSIC with a real-valued eigendecomposition: a theoretical and experimental performance study
M. Pesavento;A.B. Gershman;M. Haardt.
IEEE Transactions on Signal Processing (2000)
Maximum-likelihood direction-of-arrival estimation in the presence of unknown nonuniform noise
M. Pesavento;A.B. Gershman.
IEEE Transactions on Signal Processing (2001)
Direction finding in partly calibrated sensor arrays composed of multiple subarrays
M. Pesavento;A.B. Gershman;K.M. Wong.
IEEE Transactions on Signal Processing (2002)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: