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 (auth.), John W. Clark, Thomas Lindenau, Manfred L. Ristig (eds.)3540657371, 9783540657378

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.

---

Table of contents :
Neural networks: New tools for modelling and data analysis in science….Pages 1-96
Adaptive optics: Neural network wavefront sensing, reconstruction, and prediction….Pages 97-138
Nuclear physics with neural networks….Pages 139-169
Using neural networks to learn energy corrections in hadronic calorimeters….Pages 170-188
Neural networks for protein structure prediction….Pages 189-206
Evolution teaches neural networks to predict protein structure….Pages 207-223
An application of artificial neural networks in linguistics….Pages 224-242
Optimization with neural networks….Pages 243-256
Dynamics of networks and applications….Pages 257-288