ISBN: 9781032061726 - vlsi and hardware implementations using modern machine learning methods (17 risultati)

paperback. Condizione: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Paperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: New. 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-learning-based 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.…

Condizione: New. In English.

Paperback. Condizione: Brand New. 328 pages. 9.18x6.12x9.21 inches. In Stock.

Taschenbuch. Condizione: 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: Taylor & Francis Verlag GmbH, Kaufingerstr. 24, 80331 München, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu. …

Paperback. Condizione: New. 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-learning-based 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.…

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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-learning-based 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. 330 pp. Englisch. …

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 526.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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-learning-based 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. …