Global exponential stability of delayed Hopfield neural networks
Neural Networks
Globally exponential stability conditions for cellular neural networks with time-varying delays
Applied Mathematics and Computation
Global Asymptotic Stability Analysis of Neural Networks with Time-Varying Delays
Neural Processing Letters
Global Asymptotic Stability of Cohen-Grossberg Neural Networks with Multiple Discrete Delays
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
New results for global exponential stability of delayed cohen-grossberg neural networks
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
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The dynamics of a class of generalized neural networks with time-varying delays are analyzed. Without constructing a Lyapunov function, general sufficient conditions for the existence, uniqueness and exponential stability of an equilibrium of the neural networks are obtained by the nonlinear Lipschitz measure approach. The new criteria are mild, independent of the delays and do not require the boundedness, differentiability or monotonicity assumption of the activation functions. Moreover, the proposed results extend and improve existing ones.