Qualitative Analysis of General Discrete-Time Recurrent Neural Networks with Impulses

被引：0

作者：

Zhao, Xinquan ^{[1
]}

机构：

[1] Zhongnan Univ Econ & Law, Informat Sch, Wuhan 430074, Peoples R China

来源：

ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 1, PROCEEDINGS | 2009年 / 5551卷

关键词：

Discrete-time neural networks; Impulse; Unique equilibrium; Globally exponential stability; Instability; BRAIN-STATE; ASSOCIATIVE MEMORIES; ABSOLUTE STABILITY; DIFFERENCE SCHEME; CHAOS; EQUATIONS; MODELS;

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 article, the qualitative analysis of general discrete-time recurrent neural networks with impulses is discussed. First, a sufficient condition and a sufficient and necessary condition for existence and uniqueness of the equilibrium point of this neural networks are given with the help of degree theory; second, some sufficient rules for the global exponential stability of this neural networks are obtained by using Lyapunov function; finally the instability of the equilibrium is studied.

引用

页码：128 / 137

页数：10

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