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Radial Basis Function Networks 2

New Advances in Design

  • Book
  • © 2001

Overview

Editors:
  1. Robert J. Howlett

    1. School of Engineering, Intelligent Signal Processing Laboratories (ISP), University of Brighton, Moulsecoomb, Brighton, UK

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  2. Lakhmi C. Jain

    1. Knowledge-Based Intelligent Engineering Systems Centre, University of South Australia, Adelaide, Mawson Lakes, Australia

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    You can also search for this editor in PubMed   Google Scholar

  • Contains a wide range of applications in the laboratory and case studies describing current use
  • Overall view of the methods used for the genetic optimization of artificial neural networks and presentation of the inherent problems
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 67)

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-xix
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  2. An Overview of Radial Basis Function Networks

    • J. Ghosh, A. Nag
    Pages 1-36

  3. Using Radial Basis Function Networks for Hand Gesture Recognition

    • R. Salomon, J. Weissmann
    Pages 37-58

  4. Using Normalized RBF Networks to Map Hand Gestures to Speech

    • S. S. Fels
    Pages 59-101

  5. Face Recognition Using RBF Networks

    • A. J. Howell
    Pages 103-141

  6. Classification of Facial Expressions with Domain Gaussian RBF Networks

    • J. M. Hogan, M. Norris, J. Diederich
    Pages 143-165

  7. RBF Network Classification of ECGs as a Potential Marker for Sudden Cardiac Death

    • H. A. Kestler, F. Schwenker
    Pages 167-214

  8. Biomedical Applications of Radial Basis Function Networks

    • A. Saastamoinen, M. Lehtokangas, A. Värri, J. Saarinen
    Pages 215-268

  9. 3-D Visual Object Classification with Hierarchical Radial Basis Function Networks

    • F. Schwenker, H. A. Kestler
    Pages 269-293

  10. Controller Applications Using Radial Basis Function Networks

    • K. Takahashi
    Pages 295-317

  11. Model-Based Recurrent Neural Network for Fault Diagnosis of Nonlinear Dynamic Systems

    • C. Gan, K. Danai
    Pages 319-352

  12. Back Matter

    Pages 353-360
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Keywords

About this book

The Radial Basis Function (RBF) network has gained in popularity in recent years. This is due to its desirable properties in classification and functional approximation applications, accompanied by training that is more rapid than that of many other neural-network techniques. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of applications areas, for example, robotics, biomedical engineering, and the financial sector. The two-title series Theory and Applications of Radial Basis Function Networks provides a comprehensive survey of recent RBF network research. This volume, New Advances in Design, contains a wide range of applications in the laboratory and case-studies describing current use. The sister volume to this one, Recent Developments in Theory and Applications, covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms. The combination of the two volumes will prove extremely useful to practitioners in the field, engineers, researchers, students and technically accomplished managers.

Editors and Affiliations

  • School of Engineering, Intelligent Signal Processing Laboratories (ISP), University of Brighton, Moulsecoomb, Brighton, UK

    Robert J. Howlett

  • Knowledge-Based Intelligent Engineering Systems Centre, University of South Australia, Adelaide, Mawson Lakes, Australia

    Lakhmi C. Jain

Bibliographic Information

  • Book Title: Radial Basis Function Networks 2

  • Book Subtitle: New Advances in Design

  • Editors: Robert J. Howlett, Lakhmi C. Jain

  • Series Title: Studies in Fuzziness and Soft Computing

  • DOI: https://doi.org/10.1007/978-3-7908-1826-0

  • Publisher: Physica Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2001

  • Hardcover ISBN: 978-3-7908-1368-5Published: 27 March 2001

  • Softcover ISBN: 978-3-7908-2483-4Published: 27 March 2011

  • eBook ISBN: 978-3-7908-1826-0Published: 19 March 2013

  • Series ISSN: 1434-9922

  • Series E-ISSN: 1860-0808

  • Edition Number: 1

  • Number of Pages: XIX, 360

  • Topics: Artificial Intelligence, Pattern Recognition

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