Stability analysis for neural networks with discontinuous neuron activations and impulses

被引：0

作者：

Wu, Huaiqin ^{[1
,2
]}

Xue, Xiaoping ^{[1
]}

Zhong, Xiaozhu ^{[2
]}

机构：

[1] Harbin Inst Technol, Dept Math, Harbin 150001, Peoples R China

[2] Yanshan Univ, Coll Sci, Qinhuangdao 066004, Peoples R China

来源：

INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL | 2007年 / 3卷 / 6B期

关键词：

neural networks; global exponential stability; impulse; differential inclusions;

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, by using the fixed point theorem of differential inclusion theory and constructing suitable Lyapunov functions, we study the existence, uniqueness and global exponential stability of periodic solution for neural networks with discontinuous neuron activations and, impulses. The results show that the Forti's conjecture is true when neural networks are affected by impulses. Further, a numerical example is given to demonstrate the effectiveness of the results obtained in this paper.

引用

页码：1537 / 1548

页数：12

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