eBook: Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing: Software Optimizations and Hardware/Software Codesign (DRM PDF)
 
電子書格式: DRM PDF
作者: Sudeep Pasricha, Muhammad Shafique 
分類: Cybernetics & systems theory ,
Electronics engineering ,
Circuits & components ,
Embedded systems  
書城編號: 27492316


售價: $2074.00

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製造商: Springer Nature Switzerland
出版日期: 2023/10/09
ISBN: 9783031399329
 
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商品簡介
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 to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.
Sudeep Pasricha 作者作品表

Embedded Machine Learning for Cyber-Physical, Iot, and Edge Computing: Use Cases and Emerging Challenges (2024) (Hardcover)

Embedded Machine Learning for Cyber-Physical, Iot, and Edge Computing: Software Optimizations and Hardware/Software Codesign (2024) (Hardcover)

Embedded Machine Learning for Cyber-Physical, Iot, and Edge Computing (2023) (Hardcover)

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