Compact and Fast Machine Learning Accelerator for IoT Devices

Lieferzeit: Lieferbar innerhalb 14 Tagen

139,09 

Computer Architecture and Design Methodologies

ISBN: 981133322X
ISBN 13: 9789811333224
Autor: Huang, Hantao/Yu, Hao
Verlag: Springer Verlag GmbH
Umfang: ix, 149 S., 15 s/w Illustr., 61 farbige Illustr., 149 p. 76 illus., 61 illus. in color.
Erscheinungsdatum: 18.12.2018
Auflage: 1/2019
Produktform: Gebunden/Hardback
Einband: Gebunden

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.

Artikelnummer: 5735889 Kategorie:

Beschreibung

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.

Herstellerkennzeichnung:


Springer Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
DE

E-Mail: juergen.hartmann@springer.com

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