Scientific Applications of Neural Nets: Proceedings of the 194th W.E. Heraeus Seminar Held at Bad Honnef, Germany, 11–13 May 1998
Author:   John W. Clark ,  Thomas Lindenau ,  Manfred L. Ristig
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   Softcover reprint of the original 1st ed. 1999
Volume:   522
ISBN:  

9783662142356


Pages:   290
Publication Date:   17 April 2014
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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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


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Overview

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.

Full Product Details

Author:   John W. Clark ,  Thomas Lindenau ,  Manfred L. Ristig
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Softcover reprint of the original 1st ed. 1999
Volume:   522
Dimensions:   Width: 15.50cm , Height: 1.70cm , Length: 23.50cm
Weight:   0.474kg
ISBN:  

9783662142356


ISBN 10:   366214235
Pages:   290
Publication Date:   17 April 2014
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Neural networks: New tools for modelling 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.

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