Robust Exponential Stability for Discrete-Time Uncertain BAM Neural Networks Markovian Jump System with Time Delays

Author

Qiu, Jiqing ; Lu, Kunfeng

Author_Institution

Hebei Univ. of Sci. & Technol., Shijiazhuang, China

fYear

2009

fDate

7-9 Dec. 2009

Firstpage

103

Lastpage

106

Abstract

This paper is concerned with the problem of robust exponential stability for discrete-time BAM neural networks with mode-dependent time delays and Markovian jump parameters, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, the global exponential stability is investigated. The time delay varies in an interval and depends on the mode of operation. A new Markov process as discrete-time, discrete-state Markov process is considered. A numerical example illustrates the effectiveness of the method.

Keywords

Markov processes; asymptotic stability; delays; discrete time systems; linear matrix inequalities; neurocontrollers; robust control; uncertain systems; BAM neural networks; Lyapunov functional; Markov process; Markovian jump system; discrete-time uncertain system; linear matrix inequality; mode-dependent time delays; robust exponential stability; Control systems; Delay effects; Linear systems; Magnesium compounds; Markov processes; Neural networks; Neurons; Robust control; Robust stability; Sufficient conditions;

fLanguage

English

Publisher

ieee

Conference_Titel

Innovative Computing, Information and Control (ICICIC), 2009 Fourth International Conference on

Conference_Location

Kaohsiung

Print_ISBN

978-1-4244-5543-0

Type

conf

DOI

10.1109/ICICIC.2009.322

Filename

5412672