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Fixed-time stability of dynamical systems and fixed-time synchronization of coupled discontinuous neural networks

机译:耦合不连续神经网络的动态系统的固定时间稳定性和定时同步

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In this paper, the fixed-time stability of dynamical systems and the fixed-time synchronization of coupled discontinuous neural networks are investigated under the framework of Filippov solution. Firstly, by means of reduction to absurdity, a theorem of fixed-time stability is established and a high-precision estimation of the settling-time is given. It is shown by theoretic proof that the estimation bound of the settling time given in this paper is less conservative and more accurate compared with the classical results. Besides, as an important application, the fixed-time synchronization of coupled neural networks with discontinuous activation functions is proposed. By designing a discontinuous control law and using the theory of differential inclusions, some new criteria are derived to ensure the fixed-time synchronization of the addressed coupled networks. Finally, two numerical examples are provided to show the effectiveness and validity of the theoretical results. (C) 2017 Elsevier Ltd. All rights reserved.
机译:本文在Filippov解决方案的框架下研究了动态系统的固定时间稳定性和耦合的不连续神经网络的定时同步。首先,通过降低到荒谬,确定了定时稳定性的定理,并给出了沉降时间的高精度估计。与经典结果相比,本文给出的沉降时间的估计估计的理论证明是估计的估计较少,更准确。此外,作为一个重要的应用,提出了具有不连续激活功能的耦合神经网络的定时同步。通过设计不连续的控制法并使用差分夹杂物理论,导出了一些新标准,以确保所寻址的耦合网络的定时同步。最后,提供了两个数值例子以显示理论结果的有效性和有效性。 (c)2017 Elsevier Ltd.保留所有权利。

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