基于无穷时滞细胞神经网络的稳定性分析:连续和离散模型（英文）

夏合旦·哈力丁; 蒋海军; 王金铃

doi:10.13568/j.cnki.651094.2018.03.007

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基于无穷时滞细胞神经网络的稳定性分析:连续和离散模型（英文）

更新时间：2026-01-21

- 基于无穷时滞细胞神经网络的稳定性分析:连续和离散模型（英文）
- Journal of Xinjiang University (Natural Science Edition in Chinese and English) Vol. 35, Issue 3, Pages: 289-294(2018)
- 作者机构：
  
  新疆大学数学与系统科学学院
- 作者简介：
- 基金信息：
- DOI：10.13568/j.cnki.651094.2018.03.007
  CLC： O175
- Published：2018
- 稿件说明：
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[1]夏合旦·哈力丁,蒋海军,王金铃.基于无穷时滞细胞神经网络的稳定性分析:连续和离散模型（英文）[J],2018,35(03):289-294+313.
[1]夏合旦·哈力丁,蒋海军,王金铃.基于无穷时滞细胞神经网络的稳定性分析:连续和离散模型（英文）[J],2018,35(03):289-294+313. DOI： 10.13568/j.cnki.651094.2018.03.007.

DOI：10.13568/j.cnki.651094.2018.03.007.

摘要

首先

利用泛函微分方程、稳定性分析、Lyapunov泛函等理论

我们研究了具有无穷时滞连续细胞神经网络的动力学行为

并得到了其平衡点的存在性、唯一性以及全局指数稳定的充分条件;其次

我们利用半离散化方法

得到了连续系统的离散化模型

并对其动力学行为进行了分析;最后

我们通过数值模拟验证了本文的结论是真实有效的.

Abstract

In this paper

the stability of cellular neural networks(CNNs) is investigated. Firstly

based on the theories of functional differential equations

stability analysis and Lyapunov functional

we study the dynamical behaviors of continuous-time cellular neural networks with infinite delays and some sufficient conditions are achieved to guarantee its equilibrium point which uniquely exist

and is globally exponentially stable. Secondly

we obtain the discrete-time analogues of the continuous-time systems via the semi-discretization technique and also investigate its dynamic behaviors.Finally

the numerical simulation is used to validate the validity of proposed approaches.

关键词

Keywords

references

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