A Pattern Classification System Based on Neural Tree

王继成

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A Pattern Classification System Based on Neural Tree

更新时间：2025-12-08

- A Pattern Classification System Based on Neural Tree
- Acta Electronica Sinica Issue 7, (1997)
- 作者机构：
  
  同济大学计算机系
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP183
- Published：1997
- 稿件说明：
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[1]王继成.一个基于神经树结构的模式分类系统[J].电子学报,1997(07):107-110.

王继成. A Pattern Classification System Based on Neural Tree[J]. Acta Electronica Sinica, 1997, (7).
[1]王继成.一个基于神经树结构的模式分类系统[J].电子学报,1997(07):107-110. DOI：

王继成. A Pattern Classification System Based on Neural Tree[J]. Acta Electronica Sinica, 1997, (7). DOI：

摘要

目前，广泛应用于解决模式识别问题的方法有：分类树和层次前馈神经网络．本文提出了一种基于神经树结构的模式分类新方法．该方法使用小规模的神经网络作为分类树的节点，提取模式中非线性特征信息．实验结果表明，该方法一方面可以减小分类树用于模式识别产生的误差和分类村中节点的数目，另一方面可以缩短训练神经网络所需的时间。

Abstract

Classification trees and multilayer feed forward neural networks are two popular approaches to the pattern recognition problem. In this paper

a new pattern classification way based on neural treeis presented. This approach uses some small scale neural networks as the nodes of the classification tree to extract the nonlinear features of patterns. The experiment results have shown that this approach can decrease the error rate of pattern recognition and the number of nodes of classification tree

also can shorter the training time of neural network.

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Related Institution

Dept.of Electronic Engineering,Fudan University,Shanghai 2000433

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