Pradip Sasmal

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The convergence analysis of a low memory implementation of the Orthogonal Matching Pursuit method, which is termed Self Projected Matching Pursuit, is presented. The approach is extended to improve the sparsity ratio of a signal representation when approximating the signal by partitioning. A backward strategy, for reducing terms in a signal decomposition,(More)
In the present work, we discuss a procedure for constructing sparse binary and ternary matrices from existing two binary sensing matrices. The matrices that we construct have several attractive properties such as smaller density, which supports algorithms with low computational complexity. As an application of our method, we show that a CS matrix of general(More)
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