Presents theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence. Series: Studies in Computational Intelligence. Num Pages: 300 pages, 103 black & white illustrations, 27 black & white tables, biography. BIC Classification: UYQN. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 19. Weight in Grams: 631. . 2007. 2007th Edition. hardcover. . . . .

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Titre: Neural Networks
�diteur: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Date de parution: 2007
Langue: anglais
ISBN � 10 chiffres: 3540692258
ISBN � 13 chiffres: 9783540692256
Reliure: Couverture rigide
�tat de l'article: New

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Neural Networks: Computational Models and Applications presents important theoretical and practical issues in neural networks, including the learning algorithms of feed-forward neural networks, various dynamical properties of recurrent neural networks, winner-take-all networks and their applications in broad manifolds of computational intelligence: pattern recognition, uniform approximation, constrained optimization, NP-hard problems, and image segmentation. The book offers a compact, insightful understanding of the broad and rapidly growing neural networks domain.

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