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首页> 外文期刊>Chaos, Solitons and Fractals: Applications in Science and Engineering: An Interdisciplinary Journal of Nonlinear Science >Estimation of exponential convergence rate and exponential stability for neural networks with time-varying delay
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Estimation of exponential convergence rate and exponential stability for neural networks with time-varying delay

机译:时变时滞神经网络的指数收敛速度和指数稳定性估计

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We study the problem of estimating the exponential convergence rate and exponential stability for neural networks with time-varying delay. Some criteria for exponential stability are derived by using the linear matrix inequality (LMI) approach. They are less conservative than the existing ones. Some analytical methods are employed to investigate the bounds on the interconnection matrix and activation functions so that the systems are exponentially stable. (c) 2005 Elsevier Ltd. All rights reserved.
机译:我们研究了估计时变时滞神经网络的指数收敛速度和指数稳定性的问题。通过使用线性矩阵不等式(LMI)方法导出了一些指数稳定性标准。他们不如现有的保守。一些分析方法被用来研究互连矩阵和激活函数的界限,以使系统呈指数稳定。 (c)2005 Elsevier Ltd.保留所有权利。

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