Scientific Applications of Neural Nets
Proceedings of the 194th W.E. Heraeus Seminar Held at Bad Honnef, Germany, 11-13 May 1998
Published on 15. April 1999
Book
Hardback
XIII, 290 pages
978-3-540-65737-8 (ISBN)
Description
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.
More details
Series
Edition
1999
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
College/higher education
Professional and scholarly
Research
Illustrations
72 s/w Abbildungen, 6 farbige Abbildungen
6 Illustrations, color; 72 Illustrations, black and white; XIII, 290 p. 78 illus., 6 illus. in color.
Dimensions
Height: 23.5 cm
Width: 15.5 cm
Weight
538 gr
ISBN-13
978-3-540-65737-8 (9783540657378)
DOI
10.1007/BFb0104276
Schweitzer Classification
Other editions
Additional editions
John W. Clark | Thomas Lindenau | Manfred L. Ristig
Scientific Applications of Neural Nets
Proceedings of the 194th W.E. Heraeus Seminar Held at Bad Honnef, Germany, 11-13 May 1998
Book
04/2014
Springer
€53.49
Shipment within 7-9 days
Content
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.