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Delay decomposition approach to stability analysis for uncertain fuzzy Hopfield neural networks with time-varying delay

✍ Scribed by P. Balasubramaniam; R. Chandran

Publisher
Elsevier Science
Year
2011
Tongue
English
Weight
454 KB
Volume
16
Category
Article
ISSN
1007-5704

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✦ Synopsis

This paper is concerned with delay-dependent stability analysis for uncertain Tagaki-Sugeno (T-S) fuzzy Hopfield neural networks (UFHNNs) with time-varying delay. By decomposing the delay interval into multiple equidistant subintervals, Lyapunov-Krasovskii functionals (LKFs) are constructed on these intervals. Employing these LKFs, a new stability criterion is proposed in terms of Linear Matrix Inequalities (LMIs), which is dependent on the size of the time delay and can be easily verified by MATLAB LMI toolbox. Numerical examples are given to illustrative the effectiveness of the proposed method.

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