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Construction of compressed sensing matrixes based on the singular pseudo-symplectic space over finite fields 被引量:1
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作者 Gao You Tong Fenghua Zhang Xiaojuan 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2016年第6期82-89,共8页
Compressed sensing(CS) provides a new approach to acquire data as a sampling technique and makes it sure that a sparse signal can be reconstructed from few measurements. The construction of compressed matrixes is a ... Compressed sensing(CS) provides a new approach to acquire data as a sampling technique and makes it sure that a sparse signal can be reconstructed from few measurements. The construction of compressed matrixes is a central problem in compressed sensing. This paper provides a construction of deterministic CS matrixes, which are also disjunct and inclusive matrixes, from singular pseudo-symplectic space over finite fields of characteristic 2. Our construction is superior to De Vore's construction under some conditions and can be used to reconstruct sparse signals through an efficient algorithm. 展开更多
关键词 compressed sensing matrix singular pseudo-symplectic space sparse signal disjunct matrix inclusive matrix
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