VLSI and Hardware Implementations using Modern Machine Learning Methods
Language: English
Published by CRC Press Okt 2024, 2024
- Softcover
- New
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
AbeBooks seller since January 11, 2012
Condition: New
£ 48.38
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Add to basketItem description from seller
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.…
Seller Inventory # 9781032061726
- Title
- VLSI and Hardware Implementations using Modern Machine Learning Methods
- Author
- Sandeep Saini
- Publisher
- CRC Press Okt 2024
- Publication year
- 2024
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 1032061723
- ISBN 13
- 9781032061726
- Item weight
- 503 grams
- Dimensions
- 234x156x18 mm
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 design
- Discusses hardware implementation and device modeling pertaining to machine learning algorithms
- Explores machine learning for various VLSI architectures and reconfigurable computing
- Illustrates the latest techniques for device size and feature optimization
- Highlights the latest case studies and reviews of the methods used for hardware implementation
This book is aimed at researchers, professionals, and graduate students in VLSI, machine learning, electrical and electronic engineering, computer engineering, and hardware systems.
"Synopsis" may belong to another edition of this title.
From the Back Cover
"About the title" may belong to another edition of this title.
BuchWeltWeit Ludwig Meier e.K.
Bergisch Gladbach, Germany
AbeBooks seller since January 11, 2012
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