Titre : |
Neural networks : algorithms, applications and programming techniques |
Type de document : |
texte imprimé |
Auteurs : |
James A. Freeman, Auteur ; David M. Skapura, Auteur |
Editeur : |
London : Addison-Wesley |
Année de publication : |
1992 |
Collection : |
Computation and neural systems series |
Importance : |
XIII-401 p. |
Présentation : |
ill. |
Format : |
24 cm |
ISBN/ISSN/EAN : |
978-0-201-51376-9 |
Note générale : |
Bibliogr. p.393. index p.395-401 |
Langues : |
Anglais (eng) |
Mots-clés : |
Automatique .
Réseaux Neurones .
Intelligence Artificielle .
Algorithme. |
Index. décimale : |
62-52 Machine et processus conduits ou contrôlés automatiquement |
Résumé : |
This book provides a solid and practical introduction to neural network computational models inspired by the brain. The authors explain the basic concepts and technology underlying such models, then show how thes models cans be applied to the solution of liverse problems in science and engineering. The book's aim is not to explore every corner of current and future reserch, but to focus on what works and to present techniques useful for solving real problems |
Note de contenu : |
Au sommaire :
- Introduction to ans technology
- Adaline and madaline
- Backpropagation
- The BAM and the hopfield memory
- Simulated annealing
- The counterpropagation network
- Self-Organizing maps
- Adaptive resonance theory
- Spatiotemporal pattern classification
- The neocognitron |
Neural networks : algorithms, applications and programming techniques [texte imprimé] / James A. Freeman, Auteur ; David M. Skapura, Auteur . - London : Addison-Wesley, 1992 . - XIII-401 p. : ill. ; 24 cm. - ( Computation and neural systems series) . ISBN : 978-0-201-51376-9 Bibliogr. p.393. index p.395-401 Langues : Anglais ( eng)
Mots-clés : |
Automatique .
Réseaux Neurones .
Intelligence Artificielle .
Algorithme. |
Index. décimale : |
62-52 Machine et processus conduits ou contrôlés automatiquement |
Résumé : |
This book provides a solid and practical introduction to neural network computational models inspired by the brain. The authors explain the basic concepts and technology underlying such models, then show how thes models cans be applied to the solution of liverse problems in science and engineering. The book's aim is not to explore every corner of current and future reserch, but to focus on what works and to present techniques useful for solving real problems |
Note de contenu : |
Au sommaire :
- Introduction to ans technology
- Adaline and madaline
- Backpropagation
- The BAM and the hopfield memory
- Simulated annealing
- The counterpropagation network
- Self-Organizing maps
- Adaptive resonance theory
- Spatiotemporal pattern classification
- The neocognitron |
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