引用本文:李益国, 沈炯, 吕震中.一种新的小波神经网络结构优化设计方法[J].控制理论与应用,2003,20(3):329~331.[点击复制]
LI Yi-guo, SHEN Jiong, LU Zhen-zhong.New approach to structure optimization of wavelet neural network[J].Control Theory and Technology,2003,20(3):329~331.[点击复制]
一种新的小波神经网络结构优化设计方法
New approach to structure optimization of wavelet neural network
摘要点击 1206  全文点击 1490  投稿时间:2001-09-19  修订日期:2002-05-13
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DOI编号  10.7641/j.issn.1000-8152.2003.3.003
  2003,20(3):329-331
中文关键词  粗糙集理论  小波神经网络  小波框架  属性依赖度
英文关键词  rough sets  wavelet neural network  wavelet frame  dependency of attributes
基金项目  
作者单位E-mail
李益国, 沈炯, 吕震中 东南大学 动力工程系, 江苏 南京 210096 li-yiguo@sohu.com 
中文摘要
      针对基于框架的小波神经网络存在的网络冗余性较大的问题, 提出一种基于粗糙集理论的网络结构优化设计方法. 首先通过时频分析确定小波神经网络的初步构造; 在此基础上, 根据网络输出对隐层节点依赖度的大小去除冗余的隐层节点, 达到优化网络结构的目的, 仿真结果表明该方法是简单而有效的.
英文摘要
      Based on the rough sets theory, an approach was presented to minimize the redundancy of structure existing in wavelet neural networks. The original structure of wavelet network is obtained through time-frequency analysis. Then the redundant nodes are eliminated in light of dependency between the output of the network and the nodes in the hidden layers to optimize the structure of wavelet network. Simulation results illustrate the proposed method is simple and effective.