Stability Analysis in Higher Order Cohen-Grossberg-Type Bidirectional Associative Memory Neural Networks

Author

Xu, Rongcong ; Xia, Yonghui

Author_Institution

Coll. of Math. & Comput. Sci., Fuzhou Univ., Fuzhou

Volume

2

fYear

2008

fDate

18-20 Oct. 2008

Firstpage

552

Lastpage

559

Abstract

In this paper, we investigate the higher order Cohen-Grossberg-type bidirectional associative memory (BAM) neural networks with time delays. By using Laypunov-Kravsovskii functional and homeomorphism theory, some new sufficient conditions are established for the existence and global exponential stability of a unique equilibrium without strict conditions imposed on self regulation functions. Finally, an example and its simulations are presented to illustrate the global exponential stability of the equilibrium.

Keywords

Lyapunov methods; asymptotic stability; content-addressable storage; delays; neural nets; Cohen-Grossberg-type bidirectional associative memory neural networks; Laypunov-Kravsovskii functional; global exponential stability; homeomorphism theory; stability analysis; time delays; Associative memory; Asymptotic stability; Computer networks; Convergence; Delay effects; Educational institutions; Magnesium compounds; Mathematics; Neural networks; Stability analysis; exponential stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation, 2008. ICNC '08. Fourth International Conference on

Conference_Location

Jinan

Print_ISBN

978-0-7695-3304-9

Type

conf

DOI

10.1109/ICNC.2008.9

Filename

4667056