Compact and Fast Machine Learning Accelerator for IoT Devices (Hardcover, 1st ed. 2019)

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.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Computer Architecture and Design Methodologies
Release date:	December 2018
First published:	2019
Authors:	Hantao Huang • Hao Yu
Dimensions:	235 x 155 x 16mm (L x W x T)
Format:	Hardcover
Pages:	149
Edition:	1st ed. 2019
ISBN-13:	978-981-13-3322-4
Categories:	Books > Science & Mathematics > Mathematics > Optimization > General Books > Computing & IT > Computer hardware & operating systems > Computer architecture & logic design > General Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	981-13-3322-X
Barcode:	9789811333224

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