A new neural network for solving nonlinear convex programs with linear constraints

被引：7

作者：

Yang, Yongqing ^{[1
]}

Gao, Yun ^{[1
]}

机构：

[1] Jiangnan Univ, Sch Sci, Minist Educ, Key Lab Adv Proc Control Light Ind, Wuxi 214122, Peoples R China

来源：

NEUROCOMPUTING | 2011年 / 74卷 / 17期

基金：

中国国家自然科学基金;

关键词：

Convergence; Stability; Neural network; Convex program; INEQUALITY CONSTRAINTS; OPTIMIZATION PROBLEMS; ACTIVATION FUNCTION; SUBJECT; EQUALITY;

D O I：

10.1016/j.neucom.2011.04.026

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, a new neural network was presented for solving nonlinear convex programs with linear constrains. Under the condition that the objective function is convex, the proposed neural network is shown to be stable in the sense of Lyapunov and globally converges to the optimal solution of the original problem. Several numerical examples show the effectiveness of the proposed neural network. (C) 2011 Elsevier B.V. All rights reserved.

引用

页码：3079 / 3083

页数：5

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