Novel global exponential stability analysis for BAM neural networks with time-varying delays

Author

Chen, Yonggang ; Shoujia Huang ; Yin, Jingben ; Li, Qingbo

Author_Institution

Dept. of Math., Henan Inst. of Sci. & Technol., Xinxiang, China

fYear

2009

fDate

17-19 June 2009

Firstpage

4355

Lastpage

4360

Abstract

This paper considers the global exponential stability problem for a class of bidirectional associative memory (BAM) neural networks time-varying delays. By employing Lyapunov functional method and resorting to the less conservative technique for estimating the derivative of Lyapunov functional, the improved delay-dependent exponential stability criterion is derived in terms of linear matrix inequalities (LMIs). Numerical example is presented to illustrate the less conservativeness of the obtained result.

Keywords

Lyapunov methods; asymptotic stability; delays; linear matrix inequalities; neural nets; stability criteria; time-varying systems; Lyapunov functional method; bidirectional associative memory neural networks; delay-dependent exponential stability criterion; linear matrix inequalities; time-varying delays; Artificial neural networks; Associative memory; Delay effects; Magnesium compounds; Mathematics; Neural networks; Neurons; Stability analysis; Stability criteria; Symmetric matrices; BAM neural networks; Exponential stability; Linear matrix inequalities (LMIs); Time-varying delays;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference, 2009. CCDC '09. Chinese

Conference_Location

Guilin

Print_ISBN

978-1-4244-2722-2

Electronic_ISBN

978-1-4244-2723-9

Type

conf

DOI

10.1109/CCDC.2009.5192400

Filename

5192400