Name: Vlsi and Hardware Implementations Using Modern Machine Learning Methods (en Inglés)
Price: 68.78 USD
Availability: InStock
Author: Saini Sandeep,Lata Kusum,Sinha G. R.
ISBN: 9781032061726

portada Vlsi and Hardware Implementations Using Modern Machine Learning Methods (en Inglés)

Vlsi and Hardware Implementations Using Modern Machine Learning Methods (en Inglés)

Formato

Libro Físico

Editorial

Crc Press

Autor

Saini Sandeep,Lata Kusum,Sinha G. R.

Idioma

Inglés

N° páginas

312

Encuadernación

Tapa Blanda

ISBN13

9781032061726

N° edición

Vlsi and Hardware Implementations Using Modern Machine Learning Methods (en Inglés)

Saini Sandeep,Lata Kusum,Sinha G. R. (Autor) · Crc Press · Tapa Blanda

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Reseña del libro "Vlsi and Hardware Implementations Using Modern Machine Learning Methods (en Inglés)"

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.