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The construction of compressed sensing matrices is a central problem in compressed sensing theory. In this paper, the deterministic compressed sensing matrices with characters of finite fields are constructed and the coherence of the matrices are computed. Furthermore, the maximum sparsity of recovering the original sparse signals by using our compressed sensing matrices is obtained. Meanwhile, a comparison is made with the compressed sensing matrices constructed by DeVore based on polynomials over finite fields. In the numerical simulations, our compressed sensing matrix outperforms DeVore\u2019s matrix in the process of recovering original sparse signals. <\/jats:p>","DOI":"10.1142\/s1793830918500611","type":"journal-article","created":{"date-parts":[[2018,6,27]],"date-time":"2018-06-27T04:29:22Z","timestamp":1530073762000},"page":"1850061","source":"Crossref","is-referenced-by-count":0,"title":["Deterministic construction of compressed sensing matrices with characters over finite fields"],"prefix":"10.1142","volume":"10","author":[{"given":"Gang","family":"Wang","sequence":"first","affiliation":[{"name":"Chern Institute of Mathematics and LPMC, Nankai University, Tianjin 300071, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min-Yao","family":"Niu","sequence":"additional","affiliation":[{"name":"College of Science, Civil Aviation University of China, Tianjin 300300, P. R. 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