Global Exponential Stability Analysis in Cellular Neural Networks with Time-Varying Coefficients and Delays

Global exponential stability of cellular neural networks with time-varying coefficients and delays is considered in this paper. By utilizing a delay differential inequality, a new sufficient condition ensuring global exponential stability for cellular neural networks with time-varying coefficients and delays is presented. Since the condition does not require that the delay function be differentiable or the coefficients be bounded, the results here improve and extend those given in the earlier literature.

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