Exponential Stability for Discrete-Time Stochastic BAM Neural Networks with Discrete and Distributed Delays. (9th November 2011)

• Record Type: Journal Article
• Authors: Raja, R.; Sakthivel, R.; Marshal Anthoni, S.
• Other Names: Lin C.-K. Academic Editor.; Trinajstić N. I. Academic Editor.
• Is Part Of: ISRN discrete mathematics. Volume 2011(2011)
• Publication Date: 2011-11-09
• Subjects: Discrete mathematics -- Periodicals; Computer science -- Mathematics; Computer science -- Mathematics; Periodicals; 511.1
• DOI: 10.5402/2011/153409
• Languages: English
• ISSNs: 2090-7788

Abstract

Abstract : This paper deals with the stability analysis problem for a class of discrete-time stochastic BAM neural networks with discrete and distributed time-varying delays. By constructing a suitable Lyapunov-Krasovskii functional and employing M-matrix theory, we find some sufficient conditions ensuring the global exponential stability of the equilibrium point for stochastic BAM neural networks with time-varying delays. The conditions obtained here are expressed in terms of LMIs whose feasibility can be easily checked by MATLAB LMI Control toolbox. A numerical example is presented to show the effectiveness of the derived LMI-based stability conditions.