Common Nature of Learning in BP and Hopfieldtype Neural Networks Solving an Underdetermined System of Linear Equations

您当前的位置：

首页 >

文章列表页 >

Common Nature of Learning in BP and Hopfieldtype Neural Networks Solving an Underdetermined System of Linear Equations

更新时间：2023-12-11

- Common Nature of Learning in BP and Hopfieldtype Neural Networks Solving an Underdetermined System of Linear Equations
- Acta Scientiarum Naturalium Universitatis SunYatseni Vol. 49, Issue 2, Pages: 1-7(2010)
- 作者机构：
  
  1. 中山大学信息科学与技术学院,广东,广州,510275
  2. 中山大学软件学院,广东,广州,510275
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2010，
  
  Published Online：25 March 2010，
扫描看全文
Common Nature of Learning in BP and Hopfieldtype Neural Networks Solving an Underdetermined System of Linear Equations. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 49(2):1-7(2010)
DOI：

Common Nature of Learning in BP and Hopfieldtype Neural Networks Solving an Underdetermined System of Linear Equations. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 49(2):1-7(2010) DOI：

摘要

主要针对求解线性不定方程组的两种并行计算神经网络模型（BP和Hopfield类型神经网络）进行了探讨。BP神经网络和Hopfield类型神经网络尽管在起源、网络定义、拓扑结构和学习模式上有较大的不同，但这两类人工神经网络在相同学习率条件下求解线性不定方程组中却可以表现出相同的数学公式、学习本质和计算能力，即学习同质性。此外，分别在零初值、相同但非零初值和不同随机初值三种情况下，针对两类人工神经网络求解线性不定方程组体现出来的学习同质性进行了计算机仿真验证，并证实了两类神经网络算法的有效性。

Abstract

The online solution of underdetermined linear equations is investigated by using two types of artificial neural networks (ie.

BP and Hopfieldtype neural networks). Although they differ from each other in terms of origins

network definition

structures and learning patterns

the BP and Hopfieldtype neural networks could be exploited for solving online such underdetermined linear equations and even possess a common mathematical formulation of learning and common computational abilities. In addition

based on zero initial values

the same but nonzero initial values and different random initial values

computersimulation and verification results are given. These substantiate well the efficacy and commonness of such two types of neural networks on solving underdetermined linear equations.

关键词

不定方程BP神经网络Hopfield神经网络学习同质性

Keywords

underdetermined equationBP neural networkHopfield neural networkcommon nature of learning

references

Views

146

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Hyperspectral estimation of soil conductivity of different land use types in lakeside oasis of Bosten Lake in Xinjiang

Backcalculation of Layered Elastic Moduli Of Asphalt Pavement Using BP Neural Network

Optimization of Bridges- Parameters Based on BP Neural Network and Genetic Algorithm

Interference Suppression Based on Wavelet Packets Transform and BP Neural Network for DSSS System

BP neural network models of sap flow velocity for Pinus elliottii in degraded red soil area of Jiangxi Province

Related Author

FAN Yongzhuo

LI Xinguo

WU Kuanghuai

YANG Guoliang

HUANG Xiaoqing

HE Qinghui

TANG Liqun

XI Huifeng

Related Institution

College of Geographical Sciences and Tourism / Laboratory of Lake Environment and Resources in Arid Regions of Xinjiang， Xinjiang Normal University

School of Civil Engineering, Guangzhou University

School of Construction Engineering Maoming University



School of Building and Communication South China University of Techenology

Postal code：510275
Tel：020-84112585，84113223 Email：xuebaozr@mail.sysu.edu.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09064830号-19 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰