文章基本信息

标题：Spectral Gradient Algorithm Based on the Generalized Fiser-Burmeister Function for Sparse Solutions of LCPS
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作者：Chang Gao ; Zhensheng Yu ; Feiran Wang 等
期刊名称：Open Journal of Statistics
印刷版ISSN：2161-718X
电子版ISSN：2161-7198
出版年度：2015
卷号：05
期号：06
页码：543-551
DOI：10.4236/ojs.2015.56057
语种：English
出版社：Scientific Research Publishing
摘要：This paper considers the computation of sparse solutions of the linear complementarity problems LCP(q, M). Mathematically, the underlying model is NP-hard in general. Thus an lp(0 p < 1) regularized minimization model is proposed for relaxation. We establish the equivalent unconstrained minimization reformation of the NCP-function. Based on the generalized Fiser-Burmeister function, a sequential smoothing spectral gradient method is proposed to solve the equivalent problem. Numerical results are given to show the efficiency of the proposed method.
关键词：Linear Complementarity Problem;Sparse Solution;Spectral Gradient;Generalized Fischer-Burmeister