具有不确定时变延迟的细胞神经网络的指数稳定性

Xueli Wu, Xuan Lv, Hua Meng, Yang Li
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引用次数: 1

摘要

本文提出了一种求解具有不确定时变延迟的细胞神经网络指数稳定性的新方法。通过构造Lyapunov函数,利用线性矩阵不等式(LMI)给出了时变时滞细胞神经网络的新的依赖于时滞的指数稳定性条件。本文所建立的指数稳定的充分条件易于验证,具有较宽的适应范围。最后,通过数值算例验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exponential Stability of Cellular Neural Networks with Uncertain and Time-Varying Delay
A novel method is proposed in this note for exponential stability of cellular neural networks with uncertain and time-varying delay. New delay-dependent exponential stability conditions of cellular neural network with time-varying delay is presented by constructing Lyapunov function and using linear matrix inequality (LMI). The sufficient conditions on exponential stability established in this paper, which are easily verifiable, have a wider adaptive range. Finally, a numerical example is given to demonstrate the effect of the proposed method.
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