LMI Approach for Stationary Oscillation of Interval Neural Networks With Discrete and Distributed Time-Varying Delays Under Impulsive Perturbations

Author

Li, Xiaodi ; Shen, Jianhua

Author_Institution

Sch. of Math. Sci., Xiamen Univ., Xiamen, China

Volume

21

Issue

10

fYear

2010

Firstpage

1555

Lastpage

1563

Abstract

In this paper, a class of impulsive interval neural networks with discrete and distributed time-varying delays is discussed. Several new sufficient conditions are obtained ensuring the existence, uniqueness, and global exponential stability of periodic solution (i.e., stationary oscillation) for the addressed models based on inequality analysis techniques. The obtained results can be checked easily by the linear matrix inequality control toolbox in MATLAB. Finally, two numerical examples are given to show the effectiveness of our results.

Keywords

asymptotic stability; delays; discrete time systems; linear matrix inequalities; neural nets; nonlinear control systems; oscillations; time-varying systems; LMI; discrete time-varying delay; distributed time-varying delay; global exponential stability; impulsive interval neural network; impulsive perturbation; interval neural network; linear matrix inequality; stationary oscillation; Artificial neural networks; Biological neural networks; Delay; Linear matrix inequalities; Oscillators; Stability analysis; Symmetric matrices; Differential inequality; discrete time-varying delays; distributed time-varying delays; impulsive delay; impulsive perturbations interval neural networks; linear matrix inequality; stationary oscillation; Algorithms; Models, Neurological; Neural Networks (Computer); Nonlinear Dynamics; Stochastic Processes; Time Factors;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

ISSN

1045-9227

Type

jour

DOI

10.1109/TNN.2010.2061865

Filename

5551213