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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