Delay Dependent Exponential Stability for Fuzzy Recurrent Neural Networks with Interval Time-Varying Delay

Authors:
R. Chandran;P. Balasubramaniam
Affiliations:
Department of Mathematics, Gandhigram Rural Institute, Deemed University, Gandhigram, India 624 302 and Department of Computer Science, Government Arts College, Melur, Madurai, India 625 106;Department of Mathematics, Gandhigram Rural Institute, Deemed University, Gandhigram, India 624 302
Venue:
Neural Processing Letters
Year:
2013

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Abstract

In this paper, the problem of delay-dependent exponential stability for fuzzy recurrent neural networks with interval time-varying delay is investigated. The delay interval has been decomposed into multiple non equidistant subintervals, on these interval Lyapunov-Krasovskii functionals (LKFs) are constructed to study stability analysis. Employing these LKFs, an exponential stability criterion is proposed in terms of Linear Matrix Inequalities (LMIs) which can be easily solved by MATLAB LMI toolbox. Numerical example is given to illustrate the effectiveness of the proposed method.