Globally Exponential Stability of Equilibrium for New-Hopfield Neural Networks

YAN Yu-lian; LIAO Wen-tong

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Globally Exponential Stability of Equilibrium for New-Hopfield Neural Networks

更新时间：2025-07-16

- Globally Exponential Stability of Equilibrium for New-Hopfield Neural Networks
- Acta Electronica Sinica Vol. 36, Issue 8, Pages: 1543-1546(2008)
- 作者机构：
  
  1. 漳州师范学院物理系,福建,漳州,363000
  2. 漳州师范学院图书馆,福建,漳州,363000
  3. 漳州师范学院物理系福建漳州,363000
  4. 漳州师范学院图书馆福建漳州,363000
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP183
- Published：2008
- 稿件说明：
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YAN Yu-lian, LIAO Wen-tong. Globally Exponential Stability of Equilibrium for New-Hopfield Neural Networks[J]. Acta Electronica Sinica, 2008, 36(8): 1543-1546.
DOI：

YAN Yu-lian, LIAO Wen-tong. Globally Exponential Stability of Equilibrium for New-Hopfield Neural Networks[J]. Acta Electronica Sinica, 2008, 36(8): 1543-1546. DOI：

摘要

结合生物学最近的研究成果

提出一种具有动态突触和不同时间尺度的新型Hopfield神经网络模型.运用不动点定理、不等式技巧及Lyapunov泛函等方法

讨论了该人工神经网络在具有常时滞和变时滞两种情况下

其平衡解的存在性唯一性和全局指数稳定性.

Abstract

A new Hopfield neural networks with dynamical synapses and multiple time scales is proposed in this paper

based on some recent progresses in biological science.Fixed point theorem

inequality technique and Lyapunov functional methods have been used in this paper to study properties such as the global exponential stability

existence and uniqueness of the equilibrium solution for both constant and variable time delays.

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