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Scientific Applications of Neural Nets

Proceedings of the 194th W.E. Heraeus Seminar Held at Bad Honnef, Germany, 11–13 May 1998

  • Conference proceedings
  • © 1999

Overview

Editors:
  1. John W. Clark
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  2. Thomas Lindenau
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  3. Manfred L. Ristig
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  • Neural-network models are used in a variety of fields ranging from physics to biology and information processing
  • The articles presented in this book give a thorough overview of the state of the art
  • Includes supplementary material: sn.pub/extras

Part of the book series: Lecture Notes in Physics (LNP, volume 522)

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About this book

Neural-network models for event analysis are widely used in experimental high-energy physics, star/galaxy discrimination, control of adaptive optical systems, prediction of nuclear properties, fast interpolation of potential energy surfaces in chemistry, classification of mass spectra of organic compounds, protein-structure prediction, analysis of DNA sequences, and design of pharmaceuticals. This book, devoted to this highly interdisciplinary research area, addresses scientists and graduate students. The pedagogically written review articles range over a variety of fields including astronomy, nuclear physics, experimental particle physics, bioinformatics, linguistics, and information processing.

Keywords

Table of contents (9 papers)

  1. Front Matter

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  2. Neural networks: New tools for modelling and data analysis in science

    • John W. Clark
    Pages 1-96

  3. Adaptive optics: Neural network wavefront sensing, reconstruction, and prediction

    • Patrick C. McGuire, David G. Sandler, Michael Lloyd-Hart, Troy A. Rhoadarmer
    Pages 97-138

  4. Nuclear physics with neural networks

    • Klaus A. Gernoth
    Pages 139-169

  5. Using neural networks to learn energy corrections in hadronic calorimeters

    • João Seixas
    Pages 170-188

  6. Neural networks for protein structure prediction

    • Henrik G. Bohr
    Pages 189-206

  7. Evolution teaches neural networks to predict protein structure

    • Burkhard Rost
    Pages 207-223

  8. An application of artificial neural networks in linguistics

    • Jure Zupan
    Pages 224-242

  9. Optimization with neural networks

    • Bo Söderberg
    Pages 243-256

  10. Dynamics of networks and applications

    • R. Vilela Mendes
    Pages 257-288
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Bibliographic Information

  • Book Title: Scientific Applications of Neural Nets

  • Book Subtitle: Proceedings of the 194th W.E. Heraeus Seminar Held at Bad Honnef, Germany, 11–13 May 1998

  • Editors: John W. Clark, Thomas Lindenau, Manfred L. Ristig

  • Series Title: Lecture Notes in Physics

  • DOI: https://doi.org/10.1007/BFb0104276

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 1999

  • Softcover ISBN: 978-3-662-14235-6Published: 17 April 2014

  • eBook ISBN: 978-3-540-48980-1Published: 06 May 2007

  • Series ISSN: 0075-8450

  • Series E-ISSN: 1616-6361

  • Edition Number: 1

  • Number of Pages: XIII, 290

  • Number of Illustrations: 72 b/w illustrations, 6 illustrations in colour

  • Topics: Complex Systems, Particle and Nuclear Physics, Artificial Intelligence, Statistical Physics and Dynamical Systems

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