Exponential stability analysis of delayed memristor-based recurrent neural networks with impulse effects

Exponential stability analysis of delayed memristor-based recurrent neural networks with impulse effects
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具有脉冲效应的基于延迟忆阻器的循环神经网络的指数稳定性分析

DOI:
10.1007/s00521-015-2094-6
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发表时间:
2015-11
影响因子:
6
通讯作者:
Huang Tingwen
Huang Tingwen
中科院分区:
计算机科学3区
文献类型:
--
作者:
Wang Huamin;Duan Shukai;Li Chu;ong;Wang Lidan;Huang Tingwen

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在本文中,考虑了一个具有变时滞和脉冲效应的基于广义忆阻器的递归神经网络模型。通过使用脉冲时滞微分不等式和李雅普诺夫函数,研究了脉冲时滞……(原文最后“impulsive del”不完整)
In this paper, a generalized memristor-based recurrent neural network model with variable delays and impulse effects is considered. By using an impulsive delayed differential inequality and Lyapunov function, the exponential stability of the impulsive delayed memristor-based recurrent neural networks is investigated. Several exponential and uniform stability criteria of this impulsive delayed system are derived, which promotes the study of memristor-based recurrent neural networks. Finally, the effectiveness of obtained results is illustrated by two numerical examples.
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