Neurocomputing with time delay analysis for solving convex quadratic programming problems

被引：91

作者：

Chen, YH ^{[1
]}

Fang, SC

机构：

[1] I2 Technol, Irving, TX 75039 USA

[2] N Carolina State Univ, Raleigh, NC 27695 USA

来源：

IEEE TRANSACTIONS ON NEURAL NETWORKS | 2000年 / 11卷 / 01期

关键词：

artificial neural network; convex programming; Hopfield network; linear and quadratic programming; time-delay dynamic system;

D O I：

10.1109/72.822526

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a neural-network computational scheme with time-delay consideration for solving convex quadratic programming problems, Based on some known results, a delay margin is explicitly determined for the stability of the neural dynamics, under which the states of the neural network does not oscillate. The configuration of the proposed neural network is provided. Operational characteristics of the neural network are demonstrated via numerical examples.

引用

页码：230 / 240

页数：11

共 40 条

[11]

FORSYTHE GE, 1977, COMPUTATION METHODS

[12] DELAY-INDEPENDENT STABILITY IN BIDIRECTIONAL ASSOCIATIVE MEMORY NETWORKS [J].