Zhilin Zhang
Iterative Reweighted Algorithms for Sparse Signal Recovery with Temporally Correlated Source Vectors.
Fri, 04/29/2011 - 15:01 — SomNambulAuthors: Bhaskar D. Rao, Zhilin Zhang
Subjects: Machine Learning
AbstractIterative reweighted algorithms, as a class of algorithms for sparse signal
recovery, have been found to have better performance than their non-reweighted
counterparts. However, for solving the problem of multiple measurement vectors
(MMVs), all the existing reweighted algorithms do not account for temporal
correlation among source vectors and thus their performance degrades
significantly in the presence of correlation.Sparse Signal Recovery with Temporally Correlated Source Vectors Using Sparse Bayesian Learning.
Tue, 02/22/2011 - 16:01 — SomNambulAuthors: Bhaskar D. Rao, Zhilin Zhang
Subjects: Machine Learning
AbstractWe address the sparse signal recovery problem in the context of multiple
measurement vectors (MMV) when elements in each nonzero row of the solution
matrix are temporally correlated. Existing algorithms do not consider such
temporal correlations and thus their performance degrades significantly with
the correlations. In this work, we propose a block sparse Bayesian learning
framework which models the temporal correlations.
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