Cooling schedules for optimal annealing
Mathematics of Operations Research
Parallel simulated annealing algorithms
Journal of Parallel and Distributed Computing
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IEEE Transactions on Information Theory
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IEEE Transactions on Signal Processing - Part II
Theoretical Results on Sparse Representations of Multiple-Measurement Vectors
IEEE Transactions on Signal Processing
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IEEE Transactions on Signal Processing - Part I
Sparse solutions to linear inverse problems with multiple measurement vectors
IEEE Transactions on Signal Processing
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IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Mathematical and Computer Modelling: An International Journal
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IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Compressive MUSIC: Revisiting the Link Between Compressive Sensing and Array Signal Processing
IEEE Transactions on Information Theory
Rank Awareness in Joint Sparse Recovery
IEEE Transactions on Information Theory
Penalty for Sparse Linear and Sparse Multiple Kernel Multitask Learning
IEEE Transactions on Neural Networks
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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.