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A heuristic search algorithm for the multiple measurement vectors problem
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DOI：10.1016/j.sigpro.2014.01.002.png)
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摘要
En 中文
In this paper, we address the multiple measurement vectors problem, which is now a hot topic in the compressed sensing theory and its various applications. We propose a novel heuristic search algorithm called HSAMMV to solve the problem, which is modeled as a combinatorial optimization. HSAMMV is proposed in the framework of simulated annealing algorithm. The main innovation is to take advantage of some greedy pursuit algorithms for designing the initial solution and the generating mechanism of HSAMMV. Compared with some state-of-the-art algorithms, the numerical simulation results illustrate that HSAMMV has strong global search ability and quite good recovery performance. (C) 2014 Elsevier B.V. All rights reserved.
Keyword:
Multiple measurement vectors
Compressed sensing
Heuristic search
Simulated annealing
Greedy pursuit
期刊
IF:
3.6
论文数:
10.0K
被引数:
1.7W
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