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首页> 外文期刊>Communications in Nonlinear Science and Numerical Simulation >Stability analysis of fuzzy Markovian jumping Cohen-Grossberg BAM neural networks with mixed time-varying delays
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Stability analysis of fuzzy Markovian jumping Cohen-Grossberg BAM neural networks with mixed time-varying delays

机译:混合时变时滞模糊Markovian跳跃Cohen-Grossberg BAM神经网络的稳定性分析

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摘要

In this paper, we investigate the robust stability of uncertain fuzzy Markovian jumping Cohen-Grossberg BAM neural networks with discrete and distributed time-varying delays. A new delay-dependent stability condition is derived under uncertain switching probabilities by Takagi-Sugeno fuzzy model. Based on the linear matrix inequality (LMI) technique, upper bounds for the discrete and distributed delays are calculated using the LMI toolbox in MATLAB. Numerical examples are provided to illustrate the effectiveness of the proposed method.
机译:在本文中,我们研究了具有离散和分布时变时滞的不确定模糊Markovian跳跃Cohen-Grossberg BAM神经网络的鲁棒稳定性。利用Takagi-Sugeno模糊模型推导了不确定切换概率条件下新的时滞相关稳定性条件。基于线性矩阵不等式(LMI)技术,使用MATLAB中的LMI工具箱计算离散和分布式延迟的上限。数值算例说明了该方法的有效性。

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