Robust stability of uncertain fuzzy Cohen-Grossberg BAM neural networks with time-varying delays
Expert Systems with Applications: An International Journal
Dynamic Analysis of Delayed Fuzzy Cellular Neural Networks with Time-Varying Coefficients
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
H∞ fuzzy control for systems with repeated scalar nonlinearities and random packet losses
IEEE Transactions on Fuzzy Systems
Delay-dependent H∞ and generalized H2 filtering for delayed neural networks
IEEE Transactions on Circuits and Systems Part I: Regular Papers
ACC'09 Proceedings of the 2009 conference on American Control Conference
Global Asymptotic Stability of Fuzzy Cellular Neural Networks with Unbounded Distributed Delays
Neural Processing Letters
Expert Systems with Applications: An International Journal
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This correspondence investigates the global exponential stability problem of Takagi-Sugeno fuzzy cellular neural networks with time-varying delays (TSFDCNNs). Based on the Lyapunov-Krasovskii functional theory and linear matrix inequality technique, a less conservative delay-dependent stability criterion is derived to guarantee the exponential stability of TSFDCNNs. By constructing a Lyapunov-Krasovskii functional, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is released in the proposed delay-dependent stability criterion. Two illustrative examples are provided to verify the effectiveness of the proposed results