2000 - IEEE Fellow For the statistical analysis of subspace algorithms for harmonic retrieval.
Bhaskar D. Rao spends much of his time researching Algorithm, Artificial intelligence, Signal processing, Mathematical optimization and Bayesian inference. His work deals with themes such as Mean squared error and White noise, which intersect with Algorithm. His work carried out in the field of Artificial intelligence brings together such families of science as Machine learning, Computer vision and Pattern recognition.
Many of his research projects under Signal processing are closely connected to Systolic array with Systolic array, tying the diverse disciplines of science together. His primary area of study in Mathematical optimization is in the field of Iterative method. His Bayesian inference research includes elements of Sparse approximation, Relevance and Maximum a posteriori estimation.
Bhaskar D. Rao mainly investigates Algorithm, Communication channel, Artificial intelligence, Mathematical optimization and Control theory. Bhaskar D. Rao has researched Algorithm in several fields, including MIMO, Speech recognition and Signal processing. His studies in Communication channel integrate themes in fields like Transmitter and Electronic engineering.
His Artificial intelligence research incorporates elements of Machine learning, Computer vision and Pattern recognition. His study in Mathematical optimization is interdisciplinary in nature, drawing from both Scheduling and Applied mathematics. His work focuses on many connections between Control theory and other disciplines, such as Beamforming, that overlap with his field of interest in Power control and Iterative method.
Bhaskar D. Rao focuses on Algorithm, Bayesian inference, Artificial intelligence, Communication channel and Pattern recognition. The various areas that he examines in his Algorithm study include MIMO and Sparse matrix. His biological study spans a wide range of topics, including Prior probability, Point estimation, Expectation–maximization algorithm, Kalman filter and Signal.
His research investigates the connection between Artificial intelligence and topics such as Machine learning that intersect with issues in K-SVD. His Communication channel research includes themes of Wireless, Scheduling, Overhead and Mean squared error. His Pattern recognition study integrates concerns from other disciplines, such as Speech enhancement, Range, Speech processing and Maximum a posteriori estimation.
Bhaskar D. Rao mainly focuses on Algorithm, Artificial intelligence, Communication channel, Bayesian inference and MIMO. Bhaskar D. Rao studies Algorithm, namely Estimation theory. His Artificial intelligence research integrates issues from Machine learning and Pattern recognition.
His Communication channel research incorporates themes from Mean squared error, Wireless and Compressed sensing. Bhaskar D. Rao combines subjects such as Low complexity, Message passing, Sparse approximation, Multivariate statistics and Signal with his study of Bayesian inference. The concepts of his MIMO study are interwoven with issues in Throughput, Telecommunications link and Control theory.
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.
Sparse signal reconstruction from limited data using FOCUSS: a re-weighted minimum norm algorithm
I.F. Gorodnitsky;B.D. Rao.
IEEE Transactions on Signal Processing (1997)
An overview of limited feedback in wireless communication systems
D.J. Love;R.W. Heath;V.K.N. Lau;D. Gesbert.
IEEE Journal on Selected Areas in Communications (2008)
Sparse solutions to linear inverse problems with multiple measurement vectors
S.F. Cotter;B.D. Rao;Kjersti Engan;K. Kreutz-Delgado.
IEEE Transactions on Signal Processing (2005)
Sparse Bayesian learning for basis selection
D.P. Wipf;B.D. Rao.
IEEE Transactions on Signal Processing (2004)
Performance analysis of Root-Music
B.D. Rao;K.V.S. Hari.
IEEE Transactions on Acoustics, Speech, and Signal Processing (1989)
Dictionary learning algorithms for sparse representation
Kenneth Kreutz-Delgado;Joseph F. Murray;Bhaskar D. Rao;Kjersti Engan.
Neural Computation (2003)
Sparse channel estimation via matching pursuit with application to equalization
S.F. Cotter;B.D. Rao.
IEEE Transactions on Communications (2002)
Towards robust automatic traffic scene analysis in real-time
D. Koller;J. Weber;T. Huang;J. Malik.
international conference on pattern recognition (1994)
Sparse Signal Recovery With Temporally Correlated Source Vectors Using Sparse Bayesian Learning
Zhilin Zhang;B. D. Rao.
IEEE Journal of Selected Topics in Signal Processing (2011)
Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm
Irina F. Gorodnitsky;John S. George;Bhaskar D. Rao.
Electroencephalography and Clinical Neurophysiology (1995)
Profile was last updated on December 6th, 2021.
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