A New Steepest Descent Differential Inclusion-Based Method for Solving General Nonsmooth Convex Optimization Problems

被引：0
|
作者：
Alireza Hosseini
S. M. Hosseini
机构：
[1] Tarbiat Modares University,Department of Mathematics
来源：
Journal of Optimization Theory and Applications | 2013年 / 159卷
关键词：
Steepest descent neural network; Differential inclusion-based methods; General nonsmooth convex optimization; Convergence of trajectories;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, we investigate a steepest descent neural network for solving general nonsmooth convex optimization problems. The convergence to optimal solution set is analytically proved. We apply the method to some numerical tests which confirm the effectiveness of the theoretical results and the performance of the proposed neural network.
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页码：698 / 720
页数：22
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