Volume 35 Issue 3
Dec.  2017
Article Contents
Article Navigation >  Journal of University of Electronic Science and Technology of China  > 2006  >  35(3): 399-402

WU Yan, WANG Shou-jue. A Shunting Inhibition Neural Network Structure and Learning Algorithm[J]. Journal of University of Electronic Science and Technology of China, 2006, 35(3): 399-402.
Citation: WU Yan, WANG Shou-jue. A Shunting Inhibition Neural Network Structure and Learning Algorithm[J]. Journal of University of Electronic Science and Technology of China, 2006, 35(3): 399-402.
shu

A Shunting Inhibition Neural Network Structure and Learning Algorithm

  • 1.

    Dept. of Computer Science and Technology,Tongji University Yangpu Shanghai 200092;

  • 2.

    Lab of Artificial Neural Networks,Institute of Semiconductors,CAS Haidian Beijing 100083

  • Received Date: 2004-04-15
  • Publish Date: 2006-06-15
  • A Generalized Shunting Inhibition Neuron (GSIN) model is proposed by analyzing shortcomings of the normal shunting neuron model. A new feed forward neural network architecture based on GSIN, naming Generalized Shunting Inhibition Neural Network (GSINN), and its learning algorithm are then introduced. Finally, the GSINN is applied to several benchmark classification problems, and their performance is compared with the performances of Shunting Inhibitory Artificial Neural Network (SIANN) and BP networks, and the effectiveness of the proposed network structure and learning algorithm is verified. Experimental results show that a single GSIN and simple GSINN can outperform both the SIANN and Back Propagation (BP) network.
  • 加载中
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Get Citation
PDF
XML

Article Metrics

Article views(3770) PDF downloads(58) Cited by()

Related
Proportional views

A Shunting Inhibition Neural Network Structure and Learning Algorithm

  • 1. Dept. of Computer Science and Technology,Tongji University Yangpu Shanghai 200092;
  • 2. Lab of Artificial Neural Networks,Institute of Semiconductors,CAS Haidian Beijing 100083
  • Received Date: 2004-04-15
  • Publish Date: 2006-06-15

Abstract: A Generalized Shunting Inhibition Neuron (GSIN) model is proposed by analyzing shortcomings of the normal shunting neuron model. A new feed forward neural network architecture based on GSIN, naming Generalized Shunting Inhibition Neural Network (GSINN), and its learning algorithm are then introduced. Finally, the GSINN is applied to several benchmark classification problems, and their performance is compared with the performances of Shunting Inhibitory Artificial Neural Network (SIANN) and BP networks, and the effectiveness of the proposed network structure and learning algorithm is verified. Experimental results show that a single GSIN and simple GSINN can outperform both the SIANN and Back Propagation (BP) network.

WU Yan, WANG Shou-jue. A Shunting Inhibition Neural Network Structure and Learning Algorithm[J]. Journal of University of Electronic Science and Technology of China, 2006, 35(3): 399-402.
Citation: WU Yan, WANG Shou-jue. A Shunting Inhibition Neural Network Structure and Learning Algorithm[J]. Journal of University of Electronic Science and Technology of China, 2006, 35(3): 399-402.
shu

    HTML

Catalog

    Journal Online

    Author's Notes

    Links

    Copyright © 《电子科技大学学报》编辑部

    Address: Room 350, central building, University of Electronic Science and Technology, No.4, Section 2, Jianshe North Road, Chengdu Tel: 028-83202308,83207559 Email: xuebao@uestc.edu.cn

    本系统由 北京仁和汇智信息技术有限公司 开发 

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return