Further results on exponential stability of delayed neural networks

Xiaofan Liu, Xinge Liu, Meilan Tang
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Abstract

This paper considers exponential stability of delayed neural networks(NNs). Based on some novel integral inequalities and a modified Lyapunov-Krasovskii functional(LKF), further result on delay-dependent exponential stability is obtained for the considered delayed neural networks in form of linear matrix inequality(LMI). The effectiveness of our result in this paper is also demonstrated by a numerical example.
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延迟神经网络指数稳定性的进一步结果
研究了延迟神经网络的指数稳定性问题。基于一些新的积分不等式和改进的Lyapunov-Krasovskii泛函(LKF),进一步以线性矩阵不等式(LMI)的形式得到了所考虑的延迟神经网络的时滞相关指数稳定性的结果。最后通过数值算例验证了本文结果的有效性。
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