An Intelligent Grey Wolf Optimizer Algorithm for Distributed Compressed Sensing
Open Access
- 31 January 2018
- journal article
- research article
- Published by Hindawi Limited in Computational Intelligence and Neuroscience
- Vol. 2018, 1-10
- https://doi.org/10.1155/2018/1723191
Abstract
Distributed Compressed Sensing (DCS) is an important research area of compressed sensing (CS). This paper aims at solving the Distributed Compressed Sensing (DCS) problem based on mixed support model. In solving this problem, the previous proposed greedy pursuit algorithms easily fall into suboptimal solutions. In this paper, an intelligent grey wolf optimizer (GWO) algorithm called DCS-GWO is proposed by combining GWO and -thresholding algorithm. In DCS-GWO, the grey wolves’ positions are initialized by using the -thresholding algorithm and updated by using the idea of GWO. Inheriting the global search ability of GWO, DCS-GWO is efficient in finding global optimum solution. The simulation results illustrate that DCS-GWO has better recovery performance than previous greedy pursuit algorithms at the expense of computational complexity.Keywords
Funding Information
- National Natural Science Foundation of China (51574232)
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