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Synopsis
One of the most challenging and fascinating problems of the theory of neural nets is that of asymptotic behavior, of how a system behaves as time proceeds. This is of particular relevance to many practical applications. Here we focus on association, generalization, and representation. We turn to the last topic first. The introductory chapter, "Global Analysis of Recurrent Neural Net- works," by Andreas Herz presents an in-depth analysis of how to construct a Lyapunov function for various types of dynamics and neural coding. It includes a review of the recent work with John Hopfield on integrate-and- fire neurons with local interactions. The chapter, "Receptive Fields and Maps in the Visual Cortex: Models of Ocular Dominance and Orientation Columns" by Ken Miller, explains how the primary visual cortex may asymptotically gain its specific structure through a self-organization process based on Hebbian learning. His argu- ment since has been shown to be rather susceptible to generalization.
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- ÉditeurSpringer-Verlag New York Inc.
- Date d'édition1995
- ISBN 10 0387943684
- ISBN 13 9780387943688
- ReliureRelié
- Langueanglais
- Nombre de pages311
- ÉditeurDomany Eytan, Hemmen J. Leo Van, Schulten Klaus
- Coordonnées du fabricantnon disponible
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Models of Neural Networks III: Association, Generalization, and Representation
Edité par
SPRINGER NATURE, 1995
ISBN 10 : 0387943684
ISBN 13 : 9780387943688
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Etat : Gut. Zustand: Gut | Seiten: 311 | Sprache: Englisch | Produktart: Bücher. N° de réf. du vendeur 3325770/3
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Models of Neural Networks III Association, Generalization, and Representation. With 67 Figures.
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Springer, New York, 1996
ISBN 10 : 0387943684
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Original hardcover. xii,(2),312 pp.; 24x16 cm. " Physics of Neural Networks " Text in English. - Very good, see picture 640g. N° de réf. du vendeur 73693
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Models of Neural Networks III: Association, Generalization, and Representation (Physics of Neural Networks) (Vol 3)
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Models of Neural Networks III: Association, Generalization, and Representation (Physics of Neural Networks)
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Models of Neural Networks III: Association, Generalization, and Representation (Physics of Neural Networks)
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Models of Neural Networks III: Association, Generalization, and Representation
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Springer-Verlag New York Inc., 1995
ISBN 10 : 0387943684
ISBN 13 : 9780387943688
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Models of Neural Networks III: Association, Generalization, and Representation (Physics of Neural Networks) : Association, Generalization, and Representation
Edité par
SPRINGER NATURE, 1995
ISBN 10 : 0387943684
ISBN 13 : 9780387943688
Ancien ou d'occasion
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Gebundene Ausgabe. Etat : Sehr gut. Gebraucht - Sehr gut SG -leichte Beschädigungen oder Verschmutzungen, ungelesenes Mängelexemplar, gestempelt - One of the most challenging and fascinating problems of the theory of neural nets is that of asymptotic behavior, of how a system behaves as time proceeds. This is of particular relevance to many practical applications. Here we focus on association, generalization, and representation. We turn to the last topic first. The introductory chapter, 'Global Analysis of Recurrent Neural Net works,' by Andreas Herz presents an in-depth analysis of how to construct a Lyapunov function for various types of dynamics and neural coding. It includes a review of the recent work with John Hopfield on integrate-and fire neurons with local interactions. The chapter, 'Receptive Fields and Maps in the Visual Cortex: Models of Ocular Dominance and Orientation Columns' by Ken Miller, explains how the primary visual cortex may asymptotically gain its specific structure through a self-organization process based on Hebbian learning. His argu ment since has been shown to be rather susceptible to generalization. N° de réf. du vendeur INF1000503840
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Models of Neural Networks III: Association, Generalization, and Representation (Physics of Neural Networks)
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Models of Neural Networks III : Association, Generalization, and Representation
Edité par
Springer New York Dez 1995, 1995
ISBN 10 : 0387943684
ISBN 13 : 9780387943688
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Buch. Etat : Neu. Neuware - One of the most challenging and fascinating problems of the theory of neural nets is that of asymptotic behavior, of how a system behaves as time proceeds. This is of particular relevance to many practical applications. Here we focus on association, generalization, and representation. We turn to the last topic first. The introductory chapter, 'Global Analysis of Recurrent Neural Net works,' by Andreas Herz presents an in-depth analysis of how to construct a Lyapunov function for various types of dynamics and neural coding. It includes a review of the recent work with John Hopfield on integrate-and fire neurons with local interactions. The chapter, 'Receptive Fields and Maps in the Visual Cortex: Models of Ocular Dominance and Orientation Columns' by Ken Miller, explains how the primary visual cortex may asymptotically gain its specific structure through a self-organization process based on Hebbian learning. His argu ment since has been shown to be rather susceptible to generalization. N° de réf. du vendeur 9780387943688
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