科研之友
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摘要
Recently, by taking full exploitation to the special structure of the separable convex programming, some splitting methods have been developed. However, in some practical applications, these methods need to compute the inverse of a matrix, which maybe slow down their convergence rate, especially when the dimension of the matrix is large. To solve this issue, in this paper we shall study the Peaceman-Rachford splitting method (PRSM) by adding a proximal term to its first subproblem and get a new method named proximal Peaceman-Rachford splitting method (PPRSM). Under mild conditions, the global convergence of the PPRSM is established. Finally, the efficiency of the PPRSM is illustrated by testing some applications arising in compressive sensing.
- 出版日期2016
- 单位枣庄学院
