Scientific applications of neural nets : proceedings of the 194th W.E. Heraeus Seminar held at Bad Honnef, Germany, 11-13 May 1998
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 com...
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| Altri autori: | , |
| Natura: | Livre numérique |
| Lingua: | Anglais |
| Pubblicazione: |
Berlin [etc.] :
Springer
[20..].
Cham : Springer Nature |
| Serie: | Lecture notes in physics
522 |
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| Accesso online: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Scientific applications of neural nets, éd. John W. Clark, Manfred L. Ristig, Thomas Lindenau, Berlin, Springer, 1999, 1 vol. (XIII-288 p.), Lecture notes in physics, 3-540-65737-1 • Scientific Applications of Neural Nets, Texte imprimé, 9783662142349 • Scientific Applications of Neural Nets, Texte imprimé, 9783662142356 |
| Riassunto: | 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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| Descrizione del documento: | Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| ISBN: | 9783540489801 (PDF) |
| ISSN: | 1616-6361 |
| Accesso: | Accès en ligne pour les établissements français bénéficiaires des licences nationales Accès soumis à abonnement pour tout autre établissement Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 |