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Añadir al carritoCondición: New. First edition Includes bibliographical references and index.
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Publicado por H N H International Limited, 2021
ISBN 10: 1032061715 ISBN 13: 9781032061719
Idioma: Inglés
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Publicado por H N H International Limited, 2021
ISBN 10: 1032061715 ISBN 13: 9781032061719
Idioma: Inglés
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Añadir al carritoHardcover. Condición: Brand New. 336 pages. 9.75x6.50x0.75 inches. In Stock.
Publicado por Taylor & Francis Ltd, London, 2024
ISBN 10: 1032061723 ISBN 13: 9781032061726
Idioma: Inglés
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EUR 65,34
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Añadir al carritoPaperback. Condición: new. Paperback. Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learningbased methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques.Features:Provides the details of state-of-the-art machine learning methods used in VLSI designDiscusses hardware implementation and device modeling pertaining to machine learning algorithmsExplores machine learning for various VLSI architectures and reconfigurable computingIllustrates the latest techniques for device size and feature optimizationHighlights the latest case studies and reviews of the methods used for hardware implementationThis book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems. This book aims to provide the latest machine learning based methods, algorithms, architectures, and frameworks designed for VLSI design with focus on digital, analog and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Añadir al carritoPAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Añadir al carritoPaperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 526.
Publicado por Taylor & Francis Ltd, London, 2024
ISBN 10: 1032061723 ISBN 13: 9781032061726
Idioma: Inglés
Librería: CitiRetail, Stevenage, Reino Unido
EUR 71,84
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Añadir al carritoPaperback. Condición: new. Paperback. Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learningbased methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques.Features:Provides the details of state-of-the-art machine learning methods used in VLSI designDiscusses hardware implementation and device modeling pertaining to machine learning algorithmsExplores machine learning for various VLSI architectures and reconfigurable computingIllustrates the latest techniques for device size and feature optimizationHighlights the latest case studies and reviews of the methods used for hardware implementationThis book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems. This book aims to provide the latest machine learning based methods, algorithms, architectures, and frameworks designed for VLSI design with focus on digital, analog and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Publicado por Taylor & Francis Ltd, London, 2024
ISBN 10: 1032061723 ISBN 13: 9781032061726
Idioma: Inglés
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 89,73
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Añadir al carritoPaperback. Condición: new. Paperback. Machine learning is a potential solution to resolve bottleneck issues in VLSI via optimizing tasks in the design process. This book aims to provide the latest machine-learningbased methods, algorithms, architectures, and frameworks designed for VLSI design. The focus is on digital, analog, and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. Chapters include case studies as well as novel research ideas in the given field. Overall, the book provides practical implementations of VLSI design, IC design, and hardware realization using machine learning techniques.Features:Provides the details of state-of-the-art machine learning methods used in VLSI designDiscusses hardware implementation and device modeling pertaining to machine learning algorithmsExplores machine learning for various VLSI architectures and reconfigurable computingIllustrates the latest techniques for device size and feature optimizationHighlights the latest case studies and reviews of the methods used for hardware implementationThis book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems. This book aims to provide the latest machine learning based methods, algorithms, architectures, and frameworks designed for VLSI design with focus on digital, analog and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Librería: preigu, Osnabrück, Alemania
EUR 77,00
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. VLSI and Hardware Implementations using Modern Machine Learning Methods | Sandeep Saini (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | CRC Press | EAN 9781032061726 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 91,87
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book aims to provide the latest machine learning based methods, algorithms, architectures, and frameworks designed for VLSI design with focus on digital, analog and mixed-signal design techniques, device modeling, physical design, hardware implementation, testability, reconfigurable design, synthesis and verification, and related areas.
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 147,07
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Añadir al carritoHardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.