一类具有非线性齐次激活函数的时滞神经网络的稳定性分析

Man Wang, Boshan Chen
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引用次数: 0

摘要

研究了一类具有齐次右手边的时滞神经网络的渐近稳定性分析问题。在无时滞系统的平凡解渐近稳定和激活函数齐次的假设下,证明了任意非负时滞时滞神经网络的零解渐近稳定。通过构造Lyapunov函数,利用齐次函数的性质,得到了具有时滞的神经网络的一个新的与时滞无关的渐近稳定条件。在文章的最后,将给出一个适当的数值例子来证明主要结果的有效性。
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Stability Analysis for a class of delayed neural networks with nonlinear homogeneous activation functions
The problem of asymptotic stability analysis is investigated about a class of delayed neural networks with homogeneous right-hands sides. Under the assumption that the trivial solution of delay free system is asymptotically stable and the activation functions are homogeneous, it is proved that the zero solution of delayed neural network is asymptotically stable for arbitrary nonnegative delay. By constructing a Lyapunov function and employing the nature of homogenous function, a new delay-independent asymptotically stability condition of the neural network with delay is obtained. At the end of the article, an appropriate numerical example which can demonstrate the effectiveness of the main result will be given.
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