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Delay-dependent exponential stability for a class of neural networks with time delays

机译:一类具有时滞的神经网络的时滞相关指数稳定性

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This paper is concerned with the exponential stability of a class of delayed neural networks described by nonlinear delay differential equations of the neutral type. In terms of a linear matrix inequality (LMI), a sufficient condition guaranteeing the existence, uniqueness and global exponential stability of an equilibrium point of such a kind of delayed neural networks is proposed. This condition is dependent on the size of the time delay, which is usually less conservative than delay-independent ones. The proposed LMI condition can be checked easily by recently developed algorithms solving LMIs. Examples are provided to demonstrate the effectiveness and applicability of the proposed criteria. (c) 2005 Elsevier B.V All rights reserved.
机译:本文关注由中立型非线性时滞微分方程描述的一类时滞神经网络的指数稳定性。针对线性矩阵不等式(LMI),提出了一种保证此类延迟神经网络平衡点存在,唯一性和全局指数稳定性的充分条件。此条件取决于时间延迟的大小,通常比不依赖延迟的时间保守。可以通过最近开发的解决LMI的算法轻松检查提出的LMI条件。提供了一些示例来证明所提议标准的有效性和适用性。 (c)2005 Elsevier B.V保留所有权利。

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