Three deterministic constructions of compressed sensing matrices with low coherence

摘要

Matrices with low coherence have applications in compressed sensing and some other areas. In this paper, we present three deterministic constructions of compressed sensing matrices by using algebraic and combinatorial methods. We show that our results outperform Gaussian random matrices. Moreover, some of our matrices are binary entries, and thus can be used in the embedding operations to get more matrices with low coherence recursively.