A Dual Dynamical Neural Network Model with the Global Convergence

Liu Jun; Wang Zhaoming; Gu Deren

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A Dual Dynamical Neural Network Model with the Global Convergence

更新时间：2025-12-08

- A Dual Dynamical Neural Network Model with the Global Convergence
- Acta Electronica Sinica Issue 4, Pages: 40-44(1993)
- 作者机构：
  
  1. 电子科技大学电子工程系
  2. 电子科技大学电子工程系成都 610054
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：1993
- 稿件说明：
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[1]刘军,王兆明,顾德仁.一种具有全局收敛性的对偶动态神经网络模型[J].电子学报,1993(04):40-44.

Liu Jun, Wang Zhaoming, Gu Deren. A Dual Dynamical Neural Network Model with the Global Convergence[J]. Acta Electronica Sinica, 1993, (4): 40-44.
[1]刘军,王兆明,顾德仁.一种具有全局收敛性的对偶动态神经网络模型[J].电子学报,1993(04):40-44. DOI：

Liu Jun, Wang Zhaoming, Gu Deren. A Dual Dynamical Neural Network Model with the Global Convergence[J]. Acta Electronica Sinica, 1993, (4): 40-44. DOI：

摘要

本文提出并研究了一种具有全局收敛特性的神经网络模型。该模型的动态特性可由对偶微分方程描述

它具有从状态空间内任一初始点找出多个稳定平衡点的能力。在应用方面

它很容易发展为诸如解决全局优化问题等要求全局收敛特性的专用神经网络。

Abstract

A neural network model with the global convergence is proposed and studied in this paper. The dynamical property of this model is described by dual differential equations and it can find out several stable equilibrium points from any initial point in the state space. This model Ican be extended easily to suit for the problems which need the global convergence such as the global optimization problems.

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