Title :
Semi-deterministic ternary matrix for compressed sensing
Author :
Weizhi Lu ; Kpalma, Kidiyo ; Ronsin, Joseph
Author_Institution :
IETR, Univ. Eur. de Bretagne (UEB), Rennes, France
Abstract :
For the random {0,±1} ternary matrix, it is interesting to determine the number of nonzero elements required for good compressed sensing performance. By seeking the best RIP, this paper proposes a semi-deterministic ternary matrix, which is of deterministic nonzero positions but random signs. In practice, it presents better performance than common random ternary matrices and Gaussian random matrices.
Keywords :
compressed sensing; matrix algebra; compressed sensing; nonzero elements; semideterministic ternary matrix; Compressed sensing; Eigenvalues and eigenfunctions; Indexes; Sensors; Sparse matrices; Symmetric matrices; Vectors; RIP; compressed sensing; deterministic; random matrix; semi-deterministic; ternary matrix;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2014 Proceedings of the 22nd European
Conference_Location :
Lisbon