Asymptotic Stability and Exponential Stability of Impulsive Delayed Hopfield Neural Networks

Author:

Chen Jing1,Li Xiaodi23,Wang Dequan4

Affiliation:

1. Department of Mathematics, Shandong University, Jinan 250100, China

2. School of Mathematical Sciences, Shandong Normal University, Jinan 250014, China

3. Research Center on Logistics Optimization and Prediction of Engineering Technology, Jinan, Shandong 250014, China

4. School of Computer Science, Fudan University, Shanghai 200433, China

Abstract

A criterion for the uniform asymptotic stability of the equilibrium point of impulsive delayed Hopfield neural networks is presented by using Lyapunov functions and linear matrix inequality approach. The criterion is a less restrictive version of a recent result. By means of constructing the extended impulsive Halanay inequality, we also analyze the exponential stability of impulsive delayed Hopfield neural networks. Some new sufficient conditions ensuring exponential stability of the equilibrium point of impulsive delayed Hopfield neural networks are obtained. An example showing the effectiveness of the present criterion is given.

Funder

Project of Shandong Province Higher Educational Science and Technology Program

Publisher

Hindawi Limited

Subject

Applied Mathematics,Analysis

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