具有马尔可夫跳变参数的不确定时滞模糊Hopfield神经网络的鲁棒稳定性。

Hongyi Li, Bing Chen, Qi Zhou, Weiyi Qian
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引用次数: 310

摘要

利用Takagi-Sugeno (T-S)模糊模型研究具有马尔可夫跳变参数的非线性时滞Hopfield神经网络的鲁棒稳定性问题。首先将非线性延迟hnn建立为一个改进的T-S模糊模型,其中后部分由一组具有区间延迟的马尔可夫跳变hnn组成。这里假定时滞是时变的,属于给定的区间。基于Lyapunov-Krasovskii稳定性理论和线性矩阵不等式方法,给出了时滞上界和下界的稳定性条件。最后,通过数值算例验证了所提方法的有效性。
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Robust stability for uncertain delayed fuzzy Hopfield neural networks with Markovian jumping parameters.

This paper is concerned with the problem of the robust stability of nonlinear delayed Hopfield neural networks (HNNs) with Markovian jumping parameters by Takagi-Sugeno (T-S) fuzzy model. The nonlinear delayed HNNs are first established as a modified T-S fuzzy model in which the consequent parts are composed of a set of Markovian jumping HNNs with interval delays. Time delays here are assumed to be time-varying and belong to the given intervals. Based on Lyapunov-Krasovskii stability theory and linear matrix inequality approach, stability conditions are proposed in terms of the upper and lower bounds of the delays. Finally, numerical examples are used to illustrate the effectiveness of the proposed method.

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