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具有离散和分布式时滞的忆阻神经网络的拉格朗日稳定性。

Lagrange stability of memristive neural networks with discrete and distributed delays.

出版信息

IEEE Trans Neural Netw Learn Syst. 2014 Apr;25(4):690-703. doi: 10.1109/TNNLS.2013.2280458.

Abstract

Memristive neuromorphic system is a good candidate for creating artificial brain. In this paper, a general class of memristive neural networks with discrete and distributed delays is introduced and studied. Some Lagrange stability criteria dependent on the network parameters are derived via nonsmooth analysis and control theory. In particular, several succinct criteria are provided to ascertain the Lagrange stability of memristive neural networks with and without delays. The proposed Lagrange stability criteria are the improvement and extension of the existing results in the literature. Three numerical examples are given to show the superiority of theoretical results.

摘要

忆阻神经形态系统是构建人工大脑的理想候选方案。本文提出并研究了一类具有离散和分布式时滞的广义忆阻神经网络。通过非光滑分析和控制理论,推导出了一些依赖于网络参数的拉格朗日稳定性判据。特别地,给出了几个简洁的准则,以确定具有和不具有时滞的忆阻神经网络的拉格朗日稳定性。所提出的拉格朗日稳定性判据改进和扩展了现有文献中的结果。通过三个数值示例,验证了理论结果的优越性。

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