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Cogn Neurodyn. 2014 Jun;8(3):239-49. doi: 10.1007/s11571-013-9277-6. Epub 2014 Jan 4.
3
Impulsive control for existence, uniqueness, and global stability of periodic solutions of recurrent neural networks with discrete and continuously distributed delays.具有离散和连续分布时滞的递归神经网络周期解的存在性、唯一性和全局稳定性的脉冲控制。
IEEE Trans Neural Netw Learn Syst. 2013 Jun;24(6):868-77. doi: 10.1109/TNNLS.2012.2236352.
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Exponential input-to-state stability of recurrent neural networks with multiple time-varying delays.具有多个时变时滞的递归神经网络的指数输入状态稳定性。
Cogn Neurodyn. 2014 Feb;8(1):47-54. doi: 10.1007/s11571-013-9258-9. Epub 2013 Jun 15.
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LMI approach for stationary oscillation of interval neural networks with discrete and distributed time-varying delays under impulsive perturbations.
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Exponential stability on stochastic neural networks with discrete interval and distributed delays.具有离散区间和分布时滞的随机神经网络的指数稳定性
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7
Global asymptotic stability of reaction-diffusion Cohen-Grossberg neural networks with continuously distributed delays.具有连续分布时滞的反应扩散Cohen-Grossberg神经网络的全局渐近稳定性
IEEE Trans Neural Netw. 2010 Jan;21(1):39-49. doi: 10.1109/TNN.2009.2033910. Epub 2009 Nov 17.
8
Stability analysis of Markovian jumping stochastic Cohen-Grossberg neural networks with mixed time delays.具有混合时滞的马尔可夫跳跃随机Cohen-Grossberg神经网络的稳定性分析
IEEE Trans Neural Netw. 2008 Feb;19(2):366-70. doi: 10.1109/TNN.2007.910738.
9
Stability analysis for stochastic Cohen-Grossberg neural networks with mixed time delays.具有混合时滞的随机Cohen-Grossberg神经网络的稳定性分析
IEEE Trans Neural Netw. 2006 May;17(3):814-20. doi: 10.1109/TNN.2006.872355.

脉冲随机 Cohen-Grossberg 神经网络的稳定性与混合时滞和反应扩散项。

The stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays and reaction-diffusion terms.

机构信息

College of Electronic and Information Engineering, Southwest University, Chongqing, 400715 China ; College of Mathematics and Physics, Chongqing University of Science and Technology, Chongqing, 401331 China.

College of Electronic and Information Engineering, Southwest University, Chongqing, 400715 China.

出版信息

Cogn Neurodyn. 2015 Apr;9(2):213-20. doi: 10.1007/s11571-014-9316-y. Epub 2014 Nov 4.

DOI:10.1007/s11571-014-9316-y
PMID:25834649
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4378572/
Abstract

The global asymptotic stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays and reaction-diffusion terms is investigated. Under some suitable assumptions and using Lyapunov-Krasovskii functional method, we apply the linear matrix inequality technique to propose some new sufficient conditions for the global asymptotic stability of the addressed model in the stochastic sense. The mixed time delays comprise both the time-varying and continuously distributed delays. The effectiveness of the theoretical result is illustrated by a numerical example.

摘要

研究了具有混合时滞和反应扩散项的脉冲随机 Cohen-Grossberg 神经网络的全局渐近稳定性。在一些合适的假设下,利用 Lyapunov-Krasovskii 泛函方法,我们应用线性矩阵不等式技术,提出了该模型在随机意义下全局渐近稳定性的一些新的充分条件。混合时滞包括时变时滞和连续分布时滞。通过一个数值例子说明了理论结果的有效性。