Stability analysis and design of fuzzy control systems
Fuzzy Sets and Systems
Stability of Time-Delay Systems
Stability of Time-Delay Systems
Existence and stability of equilibria of the continuous-time Hopfield neural network
Journal of Computational and Applied Mathematics
Robust asymptotic stability of uncertain fuzzy BAM neural networks with time-varying delays
Fuzzy Sets and Systems
A survey of linear matrix inequality techniques in stability analysis of delay systems
International Journal of Systems Science
Passivity analysis of neural networks with time-varying delays
IEEE Transactions on Circuits and Systems II: Express Briefs
Hopfield neural networks for affine invariant matching
IEEE Transactions on Neural Networks
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In this paper, the global stability problem of Takagi-Sugeno (T-S) stochastic fuzzy Hopfield neural networks (TSSFHNNs) with discrete and distributed time varying delays is considered. A novel LMI-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of TSSFHNNs with discrete and distributed time varying delays. Here we choose a generalized Lyapunov functional and introduce a parameterized model transformation with free weighting matrices to it, in order to obtain 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 numerical examples. Comparison with other stability conditions in the literature shows that our conditions are the more powerful ones to guarantee the widest stability region.