Global asymptotic stability of delay bam neural networks with impulses based on matrix theory

Author

Cui, Bao-Tong ; Lou, Xu-Yang ; Huang, Min

Author_Institution

Res. Center of Control Sci. & Eng., Southern Yangtze Univ., Jiangsu, China

Volume

7

fYear

2005

fDate

18-21 Aug. 2005

Firstpage

4032

Abstract

By constructing suitable Lyapunov functional and using matrix theory, the global asymptotic stability of delay bi-directional associative memory neural networks with impulses is studied. This paper gives a sufficient condition which is independent with the delayed quantity for the global asymptotic stability of these networks. An illustrative example is given to demonstrate the effectiveness of the obtained results.

Keywords

Lyapunov matrix equations; asymptotic stability; delays; neural nets; Lyapunov functional; bidirectional associative memory neural networks; delay bam neural networks; global asymptotic stability; matrix theory; Associative memory; Asymptotic stability; Bidirectional control; Delay effects; Electronic mail; Lyapunov method; Machine learning; Magnesium compounds; Neural networks; Sufficient conditions; Bi-directional associative memory; delay; global asymptotic stability; impulse; lyapunov functional; matrix theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

Conference_Location

Guangzhou, China

Print_ISBN

0-7803-9091-1

Type

conf

DOI

10.1109/ICMLC.2005.1527643

Filename

1527643