Sparse Signal Recovery Based on Simulated Annealing

Rui Hua Liang; Xin Peng Du; Qing Bo Zhao; Li Zhi Cheng

doi:10.4028/www.scientific.net/AMM.321-324.1295

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 321-324Sparse Signal Recovery Based on Simulated...

Sparse Signal Recovery Based on Simulated Annealing

Abstract:

Sparse signal recovery is a hot topic in the fields of optimization theory and signal processing. Two main algorithmic approaches, i.e. greedy pursuit algorithms and convex relaxation algorithms have been extensively used to solve this problem. However, these algorithms cannot guarantee to find the global optimum solution, and then they perform poorly when the sparsity level is relatively large. Based on the simulated annealing algorithm and greedy pursuit algorithms, we propose a novel algorithm on solving the sparse recovery problem. Numerical simulations show that the proposed algorithm has very good recovery performance.

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Periodical:

Applied Mechanics and Materials (Volumes 321-324)

Pages:

1295-1298

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.321-324.1295

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Online since:

June 2013

Authors:

Rui Hua Liang, Xin Peng Du, Qing Bo Zhao, Li Zhi Cheng

Keywords:

Greedy Pursuit, Image Reconstruction, Simulated Annealing (SA), Sparse Recovery

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