Advances in Neural Networks - ISNN 2008

5th International Symposium on Neural Networks, ISNN 2008, Beijing, China, September 24-28, 2008, Proceedings, Part I

  • Fuchun Sun
  • Jianwei Zhang
  • Ying Tan
  • Jinde Cao
  • Wen Yu

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5263)

Table of contents

  1. Front Matter
  2. Computational Neuroscience

  3. Cognitive Science

    1. Junjie Yang, Jianzhong Zhou, Li Liu, Yinghai Li, Zhengjia Wu
      Pages 63-68
    2. Baolin Liu, Shuai Xin, Zhixing Jin, Xiaorong Gao, Shangkai Gao, Renxin Chu et al.
      Pages 97-106
    3. Baolin Liu, Shuai Xin, Zhixing Jin, Xiaorong Gao, Shangkai Gao, Renxin Chu et al.
      Pages 107-116
  4. Mathematical Modeling of Neural Systems

Other volumes

  1. Advances in Neural Networks - ISNN 2008
    5th International Symposium on Neural Networks, ISNN 2008, Beijing, China, September 24-28, 2008, Proceedings, Part I
  2. 5th International Symposium on Neural Networks, ISNN 2008, Beijing, China, September 24-28, 2008, Proceedings, Part II

About these proceedings

Introduction

The two volume set LNCS 5263/5264 constitutes the refereed proceedings of the 5th International Symposium on Neural Networks, ISNN 2008, held in Beijing, China in September 2008.

The 192 revised papers presented were carefully reviewed and selected from a total of 522 submissions. The papers are organized in topical sections on computational neuroscience; cognitive science; mathematical modeling of neural systems; stability and nonlinear analysis; feedforward and fuzzy neural networks; probabilistic methods; supervised learning; unsupervised learning; support vector machine and kernel methods; hybrid optimisation algorithms; machine learning and data mining; intelligent control and robotics; pattern recognition; audio image processinc and computer vision; fault diagnosis; applications and implementations; applications of neural networks in electronic engineering; cellular neural networks and advanced control with neural networks; nature inspired  methods of high-dimensional discrete data analysis; pattern recognition and information processing using neural networks.

Keywords

Support Vector Machine algorithms data analysis data mining machine learning modeling pattern recognition unsupervised learning

Editors and affiliations

  • Fuchun Sun
    • 1
  • Jianwei Zhang
    • 2
  • Ying Tan
    • 3
  • Jinde Cao
    • 4
  • Wen Yu
    • 5
  1. 1.Department of Computer Science and TechnologyTsinghu UniversityBeijingChina
  2. 2.Institute TAMS (Technical Aspects of Multimodal Systems), department of InformaticsUniversity of HamburgHamburgGermany
  3. 3.Intel China Research Center, 8/FPeking University, Department of Machine IntelligenceBeijingChina
  4. 4.Department of MathematicsSoutheast UniversityNanjingChina
  5. 5.Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740México D.F.México

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-87732-5
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-87731-8
  • Online ISBN 978-3-540-87732-5
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book