Stability of delayed memristive neural networks with time-varying impulses

Stability of delayed memristive neural networks with time-varying impulses
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时变脉冲延迟忆阻神经网络的稳定性

DOI:
10.1007/s11571-014-9286-0
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发表时间:
2014-03
影响因子:
3.7
通讯作者:
Huang Tingwen
Huang Tingwen
中科院分区:
工程技术2区
文献类型:
--
作者:
Qi Jiangtao;Li Chu;ong;Huang Tingwen

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研究了具有时变脉冲的忆阻神经网络的稳定性问题。在忆阻器理论和神经网络理论的基础上,建立了忆阻器神经网络模型。不同于大多数出版物的忆阻网络与固定时间的脉冲效应,我们考虑的情况下,随时间变化的脉冲。模型中同时存在失稳脉冲和稳定脉冲。通过控制稳定脉冲和失稳脉冲的时间间隔,保证了脉冲的作用效果是稳定的。提出了具有时变脉冲的忆阻神经网络全局指数稳定的几个充分条件。仿真结果验证了理论结果的有效性。
This paper addresses the stability problem on the memristive neural networks with time-varying impulses. Based on the memristor theory and neural network theory, the model of the memristor-based neural network is established. Different from the most publications on memristive networks with fixed-time impulse effects, we consider the case of time-varying impulses. Both the destabilizing and stabilizing impulses exist in the model simultaneously. Through controlling the time intervals of the stabilizing and destabilizing impulses, we ensure the effect of the impulses is stabilizing. Several sufficient conditions for the globally exponentially stability of memristive neural networks with time-varying impulses are proposed. The simulation results demonstrate the effectiveness of the theoretical results.
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