Global Exponential Stability in Delayed Hopfield Neural Network Models

LU Li; ZHANG Ji-ye; YANG Yi-ren

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Global Exponential Stability in Delayed Hopfield Neural Network Models

更新时间：2025-07-16

- Global Exponential Stability in Delayed Hopfield Neural Network Models
- Acta Electronica Sinica Vol. 30, Issue 10, Pages: 1431-1434(2002)
- 作者机构：
  
  1. 西南交通大学应用力学与工程系,四川,成都,610031
  2. 西南交通大学牵引力国家重点实验室,四川,成都,610031
  3. 西南交通大学应用力学与工程系四川成都,610031
  4. 西南交通大学牵引力国家重点实验室四川成都,610031
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP183
- Published：2002
- 稿件说明：
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LU Li, ZHANG Ji-ye, YANG Yi-ren. Global Exponential Stability in Delayed Hopfield Neural Network Models[J]. Acta Electronica Sinica, 2002, 30(10): 1431-1434.
DOI：

LU Li, ZHANG Ji-ye, YANG Yi-ren. Global Exponential Stability in Delayed Hopfield Neural Network Models[J]. Acta Electronica Sinica, 2002, 30(10): 1431-1434. DOI：

摘要

研究一类时滞Hopfield神经网络系统的平衡状态全局指数稳定性.在放宽对激励函数的可微性与单调性要求的前提下

利用矩阵理论构造适当的李雅普诺夫泛函

得到系统全局指数稳定的充分条件.

Abstract

The existence of the equilibuium and the global exponential stability of delayed Hopfield neural network models are studied.Without assuming the monotonicity and differentiability of the activation functions

by utilizing matrix theory

Liapunov functionals are constructed and employed to establish sufficient conditions for global exponential stability independen of the delays.

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