An effective algorithm for the spark of sparse binary measurement matrices

Fenghua Tong, Lixiang Li, Haipeng Peng and Yixian Yang

Applied Mathematics and Computation, 2020, vol. 371, issue C

Abstract: The spark is an important parameter to evaluate the recovery performance of measurement matrices in compressed sensing. This paper presents an effective algorithm to calculate the upper bound of the spark of sparse binary measurement matrices. Particularly, the spark of some binary measurement matrices can be accurately calculated by using our algorithm.

Keywords: Compressed sensing; Binary measurement matrices; Spark; Finite fields (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:371:y:2020:i:c:s0096300319309579

DOI: 10.1016/j.amc.2019.124965

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