计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (36): 51-52.DOI: 10.3778/j.issn.1002-8331.2008.36.014

• 理论研究 • 上一篇    下一篇

线性分类中基于感知器的子网分析法研究

陈恩伟,王 勇,陆益民,刘正士   

  1. 合肥工业大学 机械与汽车工程学院,合肥 230009
  • 收稿日期:2008-01-07 修回日期:2008-04-08 出版日期:2008-12-21 发布日期:2008-12-21
  • 通讯作者: 陈恩伟

Research on sub-network methods in linear classification based on perceptron

CHEN En-wei,WANG Yong,LU Yi-min,LIU Zheng-shi   

  1. School of Mechanical and Automotive Engineering,Hefei University of Technology,Hefei 230009,China
  • Received:2008-01-07 Revised:2008-04-08 Online:2008-12-21 Published:2008-12-21
  • Contact: CHEN En-wei

摘要: 为解决一层感知器对线性不可分矢量分类的限制,提出了一种基于一隐层感知器神经网络模型的子网分析方法。子网分析法网络构造严格精确但预处理较复杂,适合于低维矢量的分类,不会产生错分。用三维线性不可分矢量验证了这种方法的可行性。

Abstract: In order to resolve the limit of classifying the vectors of linear inseparability using perceptrons with single layer,a method of sub-network analysis is developed in this paper,which is based on the perceptrons with one hidden layer.The sub-network analysis method is strict and accurate in construction of network but more complicated in preprocessing,which is suitable for classifying low dimensional vectors and will not produce misclassifying.The feasibility of this method is proved using three dimension vectors of linear inseparability.