Compressive sensing measurement matrix construction based on improved size compatible array LDPC code

被引:15
|
作者
Yuan, Haiying [1 ]
Song, Hongying [1 ]
Sun, Xun [2 ]
Guo, Kun [1 ]
Ju, Zijian [1 ]
机构
[1] Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100124, Peoples R China
[2] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China
基金
中国国家自然科学基金;
关键词
parity check codes; compressed sensing; matrix algebra; cyclic codes; image reconstruction; image coding; compressive sensing measurement matrix construction; improved size compatible array LDPC code; ISC-array LDPC code matrix; SC-array LDPC code matrix; shift index; repetitive row elimination; RIP well; quasicyclic structure; arbitrary code length; image reconstruction quality; SIGNAL RECOVERY; DETERMINISTIC CONSTRUCTIONS; BINARY;
D O I
10.1049/iet-ipr.2015.0117
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
ISC-array LDPC code matrix is evolved from SC-array LDPC code matrix to improve compressive sensing performance for large-size sparse signal. When q is a prime number, no repetitive row occurs in the shift index of SC-array LDPC code matrix, ISC-array LDPC code matrix performs comparably with SC-array LDPC code matrix. When q is a non-prime number, some repetitive rows will appear in the shift index of SC-array LDPC code matrix, which results in more 4-cycles and decreases the compressive sensing performance. ISC-array LDPC code matrix outperforms SC-array LDPC code matrix by effectively reducing or even eliminating the repetitive rows according to their distribution rule, 4-cycles are removed to the maximum extent. ISC-array LDPC code matrix qualifies for compressive sensing because of satisfying RIP well. It also has good quasi-cyclic structure and supports arbitrary code lengths. The simulations verify that the optimised ISC-array LDPC code matrix is advantageous in the image reconstruction quality, the robustness to noise performance and the algorithm complexity.
引用
收藏
页码:993 / 1001
页数:9
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