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Compact and Fast Machine Learning Accelerator for IoT Devices (Computer Architecture and Design Methodologies) - Hardcover
Book 6 of 13: Computer Architecture and Design Methodologies
Synopsis
This book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator is presented from both algorithm level optimization and hardware architecture optimization. Coverage focuses on shallow and deep neural network with real applications on smart buildings. The authors also discuss hardware architecture design with coverage focusing on both CMOS based computing systems and the new emerging Resistive Random-Access Memory (RRAM) based systems. Detailed case studies such as indoor positioning, energy management and intrusion detection are also presented for smart buildings.
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From the Back Cover
This book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator is presented from both algorithm level optimization and hardware architecture optimization. Coverage focuses on shallow and deep neural network with real applications on smart buildings. The authors also discuss hardware architecture design with coverage focusing on both CMOS based computing systems and the new emerging Resistive Random-Access Memory (RRAM) based systems. Detailed case studies such as indoor positioning, energy management and intrusion detection are also presented for smart buildings.
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Huang:Compact and Fast Machine Learning (eng)
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Compact and Fast Machine Learning Accelerator for IoT Devices (Hardcover)
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Springer Verlag, Singapore, Singapore, 2018
ISBN 10: 981133322X
ISBN 13: 9789811333224
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Hardcover. Condition: new. Hardcover. This book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator is presented from both algorithm level optimization and hardware architecture optimization. Coverage focuses on shallow and deep neural network with real applications on smart buildings. The authors also discuss hardware architecture design with coverage focusing on both CMOS based computing systems and the new emerging Resistive Random-Access Memory (RRAM) based systems. Detailed case studies such as indoor positioning, energy management and intrusion detection are also presented for smart buildings. This book presents the latest techniques for machine learning based data analytics on IoT edge devices. The authors also discuss hardware architecture design with coverage focusing on both CMOS based computing systems and the new emerging Resistive Random-Access Memory (RRAM) based systems. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9789811333224
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Compact and Fast Machine Learning Accelerator for Iot Devices
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Springer-Verlag New York Inc, 2019
ISBN 10: 981133322X
ISBN 13: 9789811333224
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Compact and Fast Machine Learning Accelerator for Iot Devices
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Compact and Fast Machine Learning Accelerator for Iot Devices
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Compact and Fast Machine Learning Accelerator for IoT Devices
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Springer Nature Singapore, 2018
ISBN 10: 981133322X
ISBN 13: 9789811333224
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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator is presented from both algorithm level optimization and hardware architecture optimization. Coverage focuses on shallow and deep neural network with real applications on smart buildings. The authors also discuss hardware architecture design with coverage focusing on both CMOS based computing systems and the new emerging Resistive Random-Access Memory (RRAM) based systems. Detailed case studies such as indoor positioning, energy management and intrusion detection are also presented for smart buildings. Seller Inventory # 33156203/2
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Compact and Fast Machine Learning Accelerator for IoT Devices
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Springer Nature Singapore Dez 2018, 2018
ISBN 10: 981133322X
ISBN 13: 9789811333224
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator is presented from both algorithm level optimization and hardware architecture optimization. Coverage focuses on shallow and deep neural network with real applications on smart buildings. The authors also discuss hardware architecture design with coverage focusing on both CMOS based computing systems and the new emerging Resistive Random-Access Memory (RRAM) based systems. Detailed case studies such as indoor positioning, energy management and intrusion detection are also presented for smart buildings. 160 pp. Englisch. Seller Inventory # 9789811333224
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Compact and Fast Machine Learning Accelerator for IoT Devices (Computer Architecture and Design Methodologies)
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Compact and Fast Machine Learning Accelerator for Iot Devices
Published by
Springer Nature Singapore, 2018
ISBN 10: 981133322X
ISBN 13: 9789811333224
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Seller: moluna, Greven, Germany
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Offers readers a systematic and comprehensive literature review of fast and compact machine learning algorithms on IoT devicesProvides various techniques on neural network model optimization such as bit-width truncation and matrix (tensor) decompo. Seller Inventory # 251646312
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