Global exponential stability of uncertain fuzzy BAM neural networks with time-varying delays

M. Syed Ali and P. Balasubramaniam

Chaos, Solitons & Fractals, 2009, vol. 42, issue 4, 2191-2199

Abstract: In this paper, the Takagi–Sugeno (TS) fuzzy model representation is extended to the stability analysis for uncertain Bidirectional Associative Memory (BAM) neural networks with time-varying delays using linear matrix inequality (LMI) theory. A novel LMI-based stability criterion is obtained by LMI optimization algorithms to guarantee the exponential stability of uncertain BAM neural networks with time-varying delays which are represented by TS fuzzy models. Finally, the proposed stability conditions are demonstrated with numerical examples.

Date: 2009
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:42:y:2009:i:4:p:2191-2199

DOI: 10.1016/j.chaos.2009.03.138

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