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  • Conference proceedings
  • © 2009

Advances in Neural Networks - ISNN 2009

6th International Symposium on Neural Networks, ISNN 2009 Wuhan, China, May 26-29, 2009 Proceedings, Part I

Editors:

  1. Wen Yu

    1. Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, México D.F., México

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  2. Haibo He

    1. Deptartment of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, USA

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  3. Nian Zhang

    1. Dept. of Electrical and Computer Engineering, South Dakota School of Mines & Technology, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 5551)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Conference series link(s): ISNN: International Symposium on Neural Networks

Conference proceedings info: ISNN 2009.

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Table of contents (135 papers)

  1. Front Matter

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  2. Theoretical Analysis

    1. Optimal Inversion of Open Boundary Conditions Using BPNN Data-Driven Model Combined with Tidal Model

      • Mingchang Li, Guangyu Zhang, Bin Zhou, Shuxiu Liang, Zhaochen Sun
      Pages 1-10

    3. Analysis of Time-Varying EEG Based on Wavelet Packet Entropy

      • Minfen Shen, Jialiang Chen, Patch J. Beadle
      Pages 21-28

    4. A New Practical Method on Hydrological Calculation

      • Lihua Feng, Xingcai Zhang
      Pages 29-35

    7. Information Extraction System Based on Hidden Markov Model

      • Dong-Chul Park, Vu Thi Lan Huong, Dong-Min Woo, Duong Ngoc Hieu, Sai Thi Hien Ninh
      Pages 52-59

    8. Network Intrusion Detection with Workflow Feature Definition Using BP Neural Network

      • Yong Wang, Dawu Gu, Wei Li, Hongjiao Li, Jing Li
      Pages 60-67

    10. Multi-start Stochastic Competitive Hopfield Neural Network for p-Median Problem

      • Yiqiao Cai, Jiahai Wang, Jian Yin, Caiwei Li, Yunong Zhang
      Pages 75-83

    11. An Information Theoretic Perspective of the Sparse Coding

      • Hideitsu Hino, Noboru Murata
      Pages 84-93

    12. Information Dynamics and Intelligent Cooperation in Networked Societies

      • Jing Wang, Fujun Ren, Mei Zhu, Long Wang
      Pages 94-103

    14. The Bounds on the Rate of Uniform Convergence of Learning Process on Uncertainty Space

      • Xiankun Zhang, Minghu Ha, Jing Wu, Chao Wang
      Pages 110-117

    15. Adaptive Growing Quantization for 1D CMAC Network

      • Ming-Feng Yeh, Kuang-Chiung Chang
      Pages 118-127
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Other Volumes

  1. Advances in Neural Networks – ISNN 2009

  2. Advances in Neural Networks – ISNN 2009

  3. Advances in Neural Networks – ISNN 2009

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About this book

This book and its companion volumes, LNCS vols. 5551, 5552 and 5553, constitute the proceedings of the 6th International Symposium on Neural Networks (ISNN 2009), held during May 26–29, 2009 in Wuhan, China. Over the past few years, ISNN has matured into a well-established premier international symposium on neural n- works and related fields, with a successful sequence of ISNN symposia held in Dalian (2004), Chongqing (2005), Chengdu (2006), Nanjing (2007), and Beijing (2008). Following the tradition of the ISNN series, ISNN 2009 provided a high-level inter- tional forum for scientists, engineers, and educators to present state-of-the-art research in neural networks and related fields, and also to discuss with international colleagues on the major opportunities and challenges for future neural network research. Over the past decades, the neural network community has witnessed tremendous - forts and developments in all aspects of neural network research, including theoretical foundations, architectures and network organizations, modeling and simulation, - pirical study, as well as a wide range of applications across different domains. The recent developments of science and technology, including neuroscience, computer science, cognitive science, nano-technologies and engineering design, among others, have provided significant new understandings and technological solutions to move the neural network research toward the development of complex, large-scale, and n- worked brain-like intelligent systems. This long-term goal can only be achieved with the continuous efforts of the community to seriously investigate different issues of the neural networks and related fields.
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Keywords

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Editors and Affiliations

  • Departamento de Control Automático, CINVESTAV-IPN, A.P. 14-740, Av.IPN 2508, México D.F., México

    Wen Yu

  • Deptartment of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, USA

    Haibo He

  • Dept. of Electrical and Computer Engineering, South Dakota School of Mines & Technology, USA

    Nian Zhang

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Bibliographic Information

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Access via your institution

Buy it now

eBook USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

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