Neural networks: a systematic introduction
Neural networks: a systematic introduction
Global exponential stability in DCNNs with distributed delays and unbounded activations
Journal of Computational and Applied Mathematics
Delay-dependent stabilization of linear systems with time-varying state and input delays
Automatica (Journal of IFAC)
Improved global exponential stability criteria of cellular neural networks with time-varying delays
Mathematical and Computer Modelling: An International Journal
An improved global asymptotic stability criterion for delayed cellular neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Leakage Delays in T---S Fuzzy Cellular Neural Networks
Neural Processing Letters
International Journal of Automation and Computing
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
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This paper is concerned with the problem of global exponential stability analysis for a class of cellular neural networks with time-varying discrete and distributed delays (DDCNNs). A new delay-dependent sufficient condition is derived for the global exponential stability of the DDCNNs by using the integral inequality method and the newly proposed Lyapunov-Krasovskii functional. The obtained stability condition is less conservative than some of the existing results in the literature. Numerical examples are given to demonstrate the effectiveness and superiority of the proposed results.