A New Nonsymmetric Neural Network Algorithm for Unconstrained Minimax problem

Wen Xinhui

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A New Nonsymmetric Neural Network Algorithm for Unconstrained Minimax problem

更新时间：2025-12-08

- A New Nonsymmetric Neural Network Algorithm for Unconstrained Minimax problem
- Acta Electronica Sinica Issue 12, (1995)
- 作者机构：
  
  1. 中国石油天然气总公司信息中心
  2. 西安电子科技大学
  3. 中国石油信息研究所
  4. 中国石油天然气总公司信息中心西安电子科技大学中国石油信息研究所
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP18
- Published：1995
- 稿件说明：
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[1]文新辉,陈开周,牛明洁.解无约束极大极小问题的非对称神经网络算法[J].电子学报,1995(12):111-114.

Wen Xinhui. A New Nonsymmetric Neural Network Algorithm for Unconstrained Minimax problem[J]. Acta Electronica Sinica, 1995, (12).
[1]文新辉,陈开周,牛明洁.解无约束极大极小问题的非对称神经网络算法[J].电子学报,1995(12):111-114. DOI：

Wen Xinhui. A New Nonsymmetric Neural Network Algorithm for Unconstrained Minimax problem[J]. Acta Electronica Sinica, 1995, (12). DOI：

摘要

本文构造了一种新的非对称神经网络模型，用于求解极大极小无约束优化问题。并证明了非对称线性神经网络和非线性神经网络是整体Ｌｙａｐｕｎｏｖ稳定的，且收敛于对应的Ｌａｇｒａｎｇｅ方程的稳定点．计算机模拟的结果表明此方法是可行的，且具有良好的整体收敛性．

Abstract

This paper has given a new nonsymmetric neural network model

which can be used to solve unconstrained minimax problem. We have proved that nonsymmtric linear and nonlinear neural networks are Lyapunov stable and the solution is the stable point of the Lagrange equation. The computing result show that this method is better.

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