Trends in Neural Computation

  • Ke Chen
  • Lipo Wang

Part of the Studies in Computational Intelligence book series (SCI, volume 35)

Table of contents

  1. Front Matter
    Pages I-X
  2. Kar-Ann Toh, Quoc-Long Tran, Dipti Srinivasan
    Pages 1-33
  3. Jigang Wang, Predrag Neskovic, Leon N. Cooper
    Pages 61-84
  4. Takashi Kuremoto, Tsuyoshi Eto, Kunikazu Kobayashi, Masanao Obayashi
    Pages 111-133
  5. QingXiang Wu, Martin McGinnity, Liam Maguire, Bredan Glackin, Ammar Belatreche
    Pages 171-197
  6. Joseph Herbert, JingTao Yao
    Pages 199-223
  7. Chunkai Zhang, Hong Hu
    Pages 265-283
  8. Yan Liu, Bojan Cukic, Johann Schumann, Michael Jiang
    Pages 367-389
  9. Elias Kyriakides, Marios Polycarpou
    Pages 391-418
  10. Yuan Kang, Min-Hwei Chu, Min-Chou Chen
    Pages 461-481
  11. Fredrik Linåker, Masumi Ishikawa
    Pages 483-512

About this book


Nowadays neural computation has become an interdisciplinary field in its own right; researches have been conducted ranging from diverse disciplines, e.g. computational neuroscience and cognitive science, mathematics, physics, computer science, and other engineering disciplines. From different perspectives, neural computation provides an alternative methodology to understand brain functions and cognitive process and to solve challenging real-world problems effectively.

Trend in Neural Computation includes twenty chapters either contributed from leading experts or formed by extending well selected papers presented in the 2005 International Conference on Natural Computation. The edited book aims to reflect the latest progresses made in different areas of neural computation, including theoretical neural computation, biologically plausible neural modeling, computational cognitive science, artificial neural networks – architectures and learning algorithms and their applications in real-world problems. Researchers, graduate students and industrial practitioners in the broad areas of neural computation would benefit from the state-of-the-art work collected in this book.


Analysis Regression algorithm algorithms architecture artificial neural network biometrics classification computer computer science learning model modeling robot

Editors and affiliations

  • Ke Chen
    • 1
  • Lipo Wang
    • 2
  1. 1.School of Computer ScienceThe University of ManchesterManchesterUK
  2. 2.School of Electrical & Electronic EngineeringNanyang Technological UniversitySingaporeSingapore

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-540-36121-3
  • Online ISBN 978-3-540-36122-0
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
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