A New Layer-Wise Linearized Algorithm for Feedforward Neural Network

TIAN Chuan-jun; WEI Gang

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A New Layer-Wise Linearized Algorithm for Feedforward Neural Network

更新时间：2025-07-16

- A New Layer-Wise Linearized Algorithm for Feedforward Neural Network
- Acta Electronica Sinica Vol. 29, Issue 11, Pages: 1495-1498(2001)
- 作者机构：
  
  华南理工大学无线电与自动控制研究所,广东,广州,510640
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP183
- Published：2001
- 稿件说明：
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TIAN Chuan-jun, WEI Gang. A New Layer-Wise Linearized Algorithm for Feedforward Neural Network[J]. Acta Electronica Sinica, 2001, 29(11): 1495-1498.
DOI：

TIAN Chuan-jun, WEI Gang. A New Layer-Wise Linearized Algorithm for Feedforward Neural Network[J]. Acta Electronica Sinica, 2001, 29(11): 1495-1498. DOI：

摘要

本文利用数学分析的方法

提出了一种前向神经网络快速分层线性优化算法

其特点是:用新方法构造了各层的目标函数;无须计算Hessian矩阵

加快了算法的收敛速度.仿真实验表明

与传统算法如误差反传法或BP法和含势态因子(Momentum factor)的BP法以及现有的分层优化算法相比

新算法能加快收敛速度

并降低学习误差.

Abstract

This paper presents a fast layer-wise linearized algorithm for feedforward neural networks by mathematic methods with the following features:constructing target function for each layer by new methods;not calculating the Hessian matrix

thus greatly reducing the learning time.Simulation shows that the new algorithm can accelerate the convergence rate and reduce the error compared with the existing algorithms such as backpropagation (BP) algorithm

BP algorithm with momentum factor and existing layer-wise algorithms.

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