Name: Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing. Software Optimizations and Hardware/Software Codesign
Price: 135.99 USD
Availability: InStock
Author: Muhammad Shafique;Sudeep Pasricha
ISBN: 9783031399343

portada Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing. Software Optimizations and Hardware/Software Codesign

Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing. Software Optimizations and Hardware/Software Codesign

Formato

Libro Físico

Editorial

Springer International Publishing AG

Autor

Muhammad Shafique;Sudeep Pasricha

Año

2024

N° páginas

477

Encuadernación

Tapa Blanda

Dimensiones

23.50 x 15.50 cm

ISBN13

9783031399343

Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing. Software Optimizations and Hardware/Software Codesign

Muhammad Shafique;Sudeep Pasricha (Autor) · Springer International Publishing AG · Tapa Blanda

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Reseña del libro "Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing. Software Optimizations and Hardware/Software Codesign"

This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing;Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization;Describes real applications todemonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.