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Journal of Applied Mathematics and Computing

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01-10-2012 | Applied mathematics

Dynamics of fuzzy impulsive bidirectional associative memory neural networks with time-varying delays

Authors: R. Rakkiyappan, Xiaodi Li, Donal O’Regan

Published in: Journal of Applied Mathematics and Computing | Issue 1-2/2012

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Abstract

Complex nonlinear systems can be represented to a set of linear sub-models by using fuzzy sets and fuzzy reasoning via ordinary Takagi-Sugeno (TS) fuzzy models. In this paper, the exponential stability of TS fuzzy bidirectional associative memory (BAM) neural networks with impulsive effect and time-varying delays is investigated. The model of fuzzy impulsive BAM neural networks with time-varying delays established as a modified TS fuzzy model is new in which the consequent parts are composed of a set of impulsive BAM neural networks with time-varying delays. Further the exponential stability for fuzzy impulsive BAM neural networks is presented by utilizing the Lyapunov-Krasovskii functional and the linear matrix inequality (LMI) technique without tuning any parameters. In addition, an example is provided to illustrate the applicability of the result using LMI control toolbox in MATLAB.

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Title: Dynamics of fuzzy impulsive bidirectional associative memory neural networks with time-varying delays
Authors: R. Rakkiyappan
Xiaodi Li
Donal O’Regan
Publication date: 01-10-2012
Publisher: Springer-Verlag
Published in: Journal of Applied Mathematics and Computing / Issue 1-2/2012
Print ISSN: 1598-5865
Electronic ISSN: 1865-2085
DOI: https://doi.org/10.1007/s12190-012-0554-z

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