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Librería: Emile Kerssemakers ILAB, Heerlen, Holanda
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Añadir al carritoOriginal hardcover. xii,(2),312 pp.; 24x16 cm. " Physics of Neural Networks " Text in English. - Very good, see picture 640g.
Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
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Librería: Ria Christie Collections, Uxbridge, Reino Unido
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Añadir al carritoCondición: New. In.
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Añadir al carritoCondición: New. pp. 328.
Librería: Buchpark, Trebbin, Alemania
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Añadir al carritoCondición: Gut. Zustand: Gut | Seiten: 311 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 142,84
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Añadir al carritoGebundene Ausgabe. Condición: 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.
Idioma: Inglés
Publicado por Springer New York Dez 1995, 1995
ISBN 10: 0387943684 ISBN 13: 9780387943688
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 153,14
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Añadir al carritoBuch. Condición: 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.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 131,11
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Añadir al carritoCondición: New. Print on Demand pp. 328 67 Illus.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 135,72
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Añadir al carritoCondición: New. PRINT ON DEMAND pp. 328.