Journal of the Operations Research Society of China
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Recently, the l p minimization problem (p ∈ (0, 1)) for sparse signal recovery has been studied a lot because of its efficiency. In this paper, we propose a general smoothing algorithmic framework based on the entropy function for solving a class of l p minimization problems, which includes the well-known unconstrained l2–l p problem as a special case.We show that any accumulation point of the sequence generated by the proposed algorithm is a stationary point of the l p minimization problem, and derive a lower bound for the nonzero entries of the stationary point of the smoothing problem. We implement a specific version of the proposed algorithm which indicates that the entropy function-based algorithm is effective.
Key words: l p minimization problem ·, Entropy function ·, Smoothing conjugate gradient method
Yu-Fan Li· Zheng-Hai Huang · Min Zhang. Entropy Function-Based Algorithms for Solving a Class of Nonconvex Minimization Problems[J]. Journal of the Operations Research Society of China, doi: 10.1007/s40305-015-0103-1.
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URL: https://www.jorsc.shu.edu.cn/EN/10.1007/s40305-015-0103-1
https://www.jorsc.shu.edu.cn/EN/Y2015/V3/I4/441