✦ LIBER ✦

Stability analysis of uncertain fuzzy Hopfield neural networks with time delays

✍ Scribed by M. Syed Ali; P. Balasubramaniam

Publisher: Elsevier Science
Year: 2009
Tongue: English
Weight: 300 KB
Volume: 14
Category: Article
ISSN: 1007-5704
DOI: 10.1016/j.cnsns.2008.09.024

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✦ Synopsis

In this paper, the global stability problem of uncertain Takagi-Sugeno (T-S) fuzzy Hopfield neural networks with time delays (TSFHNNs) is considered. A novel LMI-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of TSFHNNs. Here, we choose a generalized Lyapunov functional and introduce a parameterized model transformation with free weighting matrices to it, in order to obtain generalized stability region. In fact, these techniques lead to generalized and less conservative stability condition that guarantee the wide stability region. The proposed stability conditions are demonstrated with four numerical examples. Comparison with other stability conditions in the literature shows our conditions are the more powerful ones to guarantee the widest stability region.

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