Skip to main content
SpringerLink
Log in
Book cover

Advances in Neural Networks - ISNN 2009

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

  • Conference proceedings
  • © 2009

Overview

Editors:
  1. Wen Yu

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

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Haibo He

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

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Nian Zhang

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

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

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)

Included in the following conference series:

Conference proceedings info: ISNN 2009.

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
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

Licence this eBook for your library

Institutional subscriptions

Table of contents (135 papers)

  1. Front Matter

    Download chapter PDF

  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

    2. Time-Varying Matrix Square Roots Solving via Zhang Neural Network and Gradient Neural Network: Modeling, Verification and Comparison

      • Yunong Zhang, Yiwen Yang, Ning Tan
      Pages 11-20

    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

    5. Bernoulli Neural Network with Weights Directly Determined and with the Number of Hidden- Layer Neurons Automatically Determined

      • Yunong Zhang, Gongqin Ruan
      Pages 36-45

    6. Extension of Stochastic Dynamical System Involving Generalized Brownian Functionals

      • Lin Yu
      Pages 46-51

    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

    9. Features of Hodgkin-Huxley Neuron Response to Periodic Spike-Train Inputs

      • Zeng An, Liu Yan, Chen Liujun
      Pages 68-74

    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

    13. Statistical Dependency of Image Wavelet Coefficients: Full Bayesian Model for Neural Networks

      • Xingming Long, Jing Zhou
      Pages 104-109

    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

    16. Qualitative Analysis of General Discrete-Time Recurrent Neural Networks with Impulses

      • Xinquan Zhao
      Pages 128-137

    17. Simulation Study of CPG Model: Exploring of a Certain Characteristics of Rhythm of Gait Movement on the Intelligent Creature

      • Wei Dong, Rubin Wang, Zhikang Zhang
      Pages 138-148

    18. Recognition of Altered Rock Based on Improved Particle Swarm Neural Network

      • Yunjun Zhan, Yanyan Wu
      Pages 149-155

    19. Development of Design Strategy for RBF Neural Network with the Aid of Context-Based FCM

      • Ho-Sung Park, Sung-Kwun Oh, Hyun-Ki Kim
      Pages 156-163
Back to top

Other volumes

  1. Advances in Neural Networks – ISNN 2009

  2. Advances in Neural Networks – ISNN 2009

  3. Advances in Neural Networks – ISNN 2009

Keywords

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.

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

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation