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The Sparsity Adaptive Reconstruction Algorithm Based on Simulated Annealing for Compressed Sensing
Joint Authors
Sun, Guiling
Li, Yangyang
Zhang, Jianping
Lu, Dongxue
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-07-14
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
This paper proposes a novel sparsity adaptive simulated annealing algorithm to solve the issue of sparse recovery.
This algorithm combines the advantage of the sparsity adaptive matching pursuit (SAMP) algorithm and the simulated annealing method in global searching for the recovery of the sparse signal.
First, we calculate the sparsity and the initial support collection as the initial search points of the proposed optimization algorithm by using the idea of SAMP.
Then, we design a two-cycle reconstruction method to find the support sets efficiently and accurately by updating the optimization direction.
Finally, we take advantage of the sparsity adaptive simulated annealing algorithm in global optimization to guide the sparse reconstruction.
The proposed sparsity adaptive greedy pursuit model has a simple geometric structure, it can get the global optimal solution, and it is better than the greedy algorithm in terms of recovery quality.
Our experimental results validate that the proposed algorithm outperforms existing state-of-the-art sparse reconstruction algorithms.
American Psychological Association (APA)
Li, Yangyang& Zhang, Jianping& Sun, Guiling& Lu, Dongxue. 2019. The Sparsity Adaptive Reconstruction Algorithm Based on Simulated Annealing for Compressed Sensing. Journal of Electrical and Computer Engineering،Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1173792
Modern Language Association (MLA)
Li, Yangyang…[et al.]. The Sparsity Adaptive Reconstruction Algorithm Based on Simulated Annealing for Compressed Sensing. Journal of Electrical and Computer Engineering No. 2019 (2019), pp.1-8.
https://search.emarefa.net/detail/BIM-1173792
American Medical Association (AMA)
Li, Yangyang& Zhang, Jianping& Sun, Guiling& Lu, Dongxue. The Sparsity Adaptive Reconstruction Algorithm Based on Simulated Annealing for Compressed Sensing. Journal of Electrical and Computer Engineering. 2019. Vol. 2019, no. 2019, pp.1-8.
https://search.emarefa.net/detail/BIM-1173792
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1173792