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A Semi-blind Greedy Support Recovery Algorithm with Adjustable Stop Threshold
- Source :
- ICCT
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- Greedy algorithm is an important class of sparse recovery algorithm of compressive sensing. Most existing greedy recovery algorithms need the prior knowledge of the signal’s sparsity, which is unknown or even time-varying in actual applications, to determine the stop threshold of the iterative recovery process. Recently, the power of the residual signal is used to compare with the noise power to determine whether there is some sparse signal remaining. In this paper, the statistical property of the residual signal power is proved to follow the chi square distribution with parameter L(M-k), where L and M and the size of the observation matrix, and k is the recovery iteration times. Then, a semi-blind greedy algorithm is proposed, in which the stop threshold is adjust according to the recovery times. Simulation results illustrate that the proposed algorithm is more effective than the existing energy-based support recovery algorithm.
- Subjects :
- Computer science
020206 networking & telecommunications
020302 automobile design & engineering
02 engineering and technology
Residual
Signal
Compressed sensing
0203 mechanical engineering
0202 electrical engineering, electronic engineering, information engineering
Symmetric matrix
Greedy algorithm
Algorithm
Energy (signal processing)
Sparse matrix
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2020 IEEE 20th International Conference on Communication Technology (ICCT)
- Accession number :
- edsair.doi...........2152e5f4dabffb8ff5f53b1be5067851