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Composition of Binary Compressed Sensing Matrices

Sasmal, Pradip and Naidu, R Ramu and Sastry, Challa S and Jampana, Phanindra (2017) Composition of Binary Compressed Sensing Matrices. In: IEEE SIGNAL PROCESSING LETTERS, 23 (8). pp. 1096-1100.

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Official URL: http://dx.doi.org/10.1109/LSP.2016.2585181


In the recent past, various methods have been proposed to construct deterministic compressed sensing ( CS) matrices. Of interest has been the construction of binary sensing matrices as they are useful for multiplierless and faster dimensionality reduction. Inmost of these binary constructions, the matrix size depends on primes or their powers. In this study, we propose a composition rule which exploits sparsity and block structure of existing binary CS matrices to construct matrices of general size. We also show that these matrices satisfy optimal theoretical guarantees and have similar density compared to matrices obtained using Kronecker product. Simulation work shows that the synthesized matrices provide comparable results against Gaussian random matrices.

Item Type: Journal Article
Additional Information: Copy right for this article belongs to the IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 17 Jun 2017 04:11
Last Modified: 17 Jun 2017 04:11
URI: http://eprints.iisc.ac.in/id/eprint/57241

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