Solving quadratic programming problems by delayed projection neural network

被引：73
|
作者：
Yang, Yongqing [1 ]
Cao, Jinde
机构：
[1] Southeast Univ, Dept Math, Nanjing 210096, Peoples R China
[2] So Yangtze Univ, Sch Sci, Wuxi 214122, Peoples R China
来源：
IEEE TRANSACTIONS ON NEURAL NETWORKS | 2006年 / 17卷 / 06期
基金：
中国国家自然科学基金;
关键词：
convex quadratic programming; delay; neural network; stability;
D O I：
10.1109/TNN.2006.880579
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 letter, the delayed projection neural network for solving convex quadratic programming problems is proposed. The neural network is proved to be globally exponentially stable and can converge to an optimal solution of the optimization problem. Three examples show the effectiveness of the proposed network.
引用
收藏
页码：1630 / 1634
页数：5
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