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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 / John W. Clark, Thomas Lindenau, Manfred L. Ristig (eds.).

By: Contributor(s): Material type: TextTextSeries: Lecture notes in physics ; 522.Publication details: Berlin ; New York : Springer, 1999.Description: 1 online resource (xiii, 288 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540489801
  • 3540489800
Subject(s): Genre/Form: Additional physical formats: Print version:: Scientific applications of neural nets.DDC classification:
  • 502.85/632 21
LOC classification:
  • Q183.9 .W17 1998
Other classification:
  • ST 300
  • UD 8220
  • PN 95
Online resources:
Contents:
Neural Networks: New Tools for Modeling and Data Analysis in Science -- Adaptive Optics: Neural Network Wavefront Sensing, Reconstruction and Prediction -- Nuclear Physics with Neural Networks -- Using Neural Networks to Learn Energy Corrections in Hadronic Calorimeters -- Neural Networks for Protein Structure Prediction -- Evolution Teaches Neural Networks to Predict Protein Structure -- An Application of Artificial Neural Networks in Linguistics -- Optimization with Neural Networks -- Dynamics of Networks and Applications.
Action note:
  • digitized 2010 HathiTrust Digital Library committed to preserve
Summary: 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.
Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
eBook eBook e-Library eBook LN Physics Available
Total holds: 0

Includes bibliographical references.

Neural Networks: New Tools for Modeling and Data Analysis in Science -- Adaptive Optics: Neural Network Wavefront Sensing, Reconstruction and Prediction -- Nuclear Physics with Neural Networks -- Using Neural Networks to Learn Energy Corrections in Hadronic Calorimeters -- Neural Networks for Protein Structure Prediction -- Evolution Teaches Neural Networks to Predict Protein Structure -- An Application of Artificial Neural Networks in Linguistics -- Optimization with Neural Networks -- Dynamics of Networks and Applications.

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.

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Master and use copy. Digital master created according to Benchmark for Faithful Digital Reproductions of Monographs and Serials, Version 1. Digital Library Federation, December 2002. MiAaHDL

http://purl.oclc.org/DLF/benchrepro0212

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