Global Exponential Stability of Discrete-Time BAM Neural Networks With Variable Delays

Author

Liu, Xin-Ge ; Wu, Min ; Tang, Mei-Lan ; Liu, Xin-Bi

fYear

2007

fDate

May 30 2007-June 1 2007

Firstpage

3139

Lastpage

3143

Abstract

Without the boundedness assumption for the activation functions and without any extra constraints on variable delay functions, based on Lyapunov functional, homeomorphism map, techniques of inequalities and linear matrix inequality(LMI), a new delay-dependent stability criterion for (i) existence (ii) uniqueness and (iii) globally exponential stability of equilibrium point, of a class of discrete-time bidirectional associative memory (BAM) neural networks with variable delays is derived.

Keywords

asymptotic stability; content-addressable storage; delay systems; discrete time systems; linear matrix inequalities; neural nets; transfer functions; Lyapunov functional; activation functions; boundedness assumption; delay-dependent stability criterion; discrete-time BAM neural networks; discrete-time bidirectional associative memory neural networks; global exponential stability; homeomorphism map; linear matrix inequality; variable delay functions; variable delays; Automatic control; Automation; Centralized control; Delay; Linear matrix inequalities; Magnesium compounds; Neural networks; Neurons; Stability criteria; Symmetric matrices;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Automation, 2007. ICCA 2007. IEEE International Conference on

Conference_Location

Guangzhou

Print_ISBN

978-1-4244-0817-7

Electronic_ISBN

978-1-4244-0818-4

Type

conf

DOI

10.1109/ICCA.2007.4376940

Filename

4376940