Models Neural Networks Iii (33 results)

Hardcover. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!

Hardcover. Condition: New. In shrink wrap. Looks like an interesting title!

Original hardcover. xii,(2),312 pp.; 24x16 cm. " Physics of Neural Networks " Text in English. - Very good, see picture 640g.

Condition: New.

Condition: New.

Condition: New. SUPER FAST SHIPPING.

Condition: New. SUPER FAST SHIPPING.

Paperback. Condition: new. Paperback. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New.

Condition: New.

Hardcover. Condition: new. Hardcover. This collection of articles by leading researchers in neural networks responds to the urgent need for timely and comprehensive reviews in a multidisciplinary, rapidly developing field of research. It continues the themes of the previous volume, but shifts its focus to more practical matters, such as data storage and retrieval, and the recognition of handwriting. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

Condition: New. In.

Condition: New. In.

Condition: New. pp. 328.

Condition: New. pp. 328.

Condition: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher.

Condition: New. Presents a collection of articles by leading researchers in neural networks. This work focuses on data storage and retrieval, and the recognition of handwriting. Editor(s): Domany, Eytan; Van, Hemmen J. L.; Schulten, K. (Beckmann Institute for Advanced Science and Technology, Urband, Illinois, USA). Series: Physics of Neural Networks. Num Pages: 324 pages, biography. BIC Classification: UYQN. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 19. Weight in Grams: 636. . 1995. Hardback. . . . .

Taschenbuch. Condition: 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 328 pp. Englisch.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Condition: New. Presents a collection of articles by leading researchers in neural networks. This work focuses on data storage and retrieval, and the recognition of handwriting. Editor(s): Domany, Eytan; Van, Hemmen J. L.; Schulten, K. (Beckmann Institute for Advanced Science and Technology, Urband, Illinois, USA). Series: Physics of Neural Networks. Num Pages: 324 pages, biography. BIC Classification: UYQN. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 19. Weight in Grams: 636. . 1995. Hardback. . . . . Books ship from the US and Ireland.

Gebundene Ausgabe. Condition: 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.

Paperback. Condition: new. Paperback. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Buch. Condition: 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.

Hardcover. Condition: new. Hardcover. This collection of articles by leading researchers in neural networks responds to the urgent need for timely and comprehensive reviews in a multidisciplinary, rapidly developing field of research. It continues the themes of the previous volume, but shifts its focus to more practical matters, such as data storage and retrieval, and the recognition of handwriting. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - 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. 328 pp. Englisch.

Condition: New. Print on Demand pp. 328 67 Illus.

Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 489.

Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 666.