A New Neural Network for Solving Nonlinear Programming Problems

被引：0

作者：

Gao, Yun ^{[1
]}

Xu, Xianyun ^{[1
]}

Yang, Yongqing ^{[1
]}

机构：

[1] Jiangnan Univ, Sch Sci, Wuxi 214122, Peoples R China

来源：

ADVANCES IN NEURAL NETWORKS - ISNN 2011, PT I | 2011年 / 6675卷

关键词：

asymptotical stability; neural network; nonlinear programming; OPTIMIZATION PROBLEMS; LINEAR CONSTRAINTS; SUBJECT;

D O I：

暂无

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 is proposed to solve nonlinear convex programming problems. The proposed neural network is shown to be asymptotically stable in the sense of Lyapunov. Comparing with the existing neural networks, the proposed neural network has fewer state variables and simpler architecture. Numerical examples show that the proposed network is feasible and efficient.

引用

页码：565 / 571

页数：7

共 23 条

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[Anonymous], 1982, ORDINARY DIFFERENTIA

[2]

[Anonymous], 1993, Neural networks for optimization and signal processing

[3]

Avriel M., 2003, NONLINEAR PROGRAMMIN

[4]

Bazaraa M. S., 2006, NONLINEAR PROGRAMMIN