Neuro-inspired Computing Using Resistive Synaptic Devices

By: Shimeng Yu (Editor)

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Paperback | 25 July 2018

At a Glance

Paperback
269 Pages

Dimensions(cm)
23.5 x 15.5

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This book summarizes the recent breakthroughs in hardware implementation of neuro-inspired computing using resistive synaptic devices. The authors describe how two-terminal solid-state resistive memories can emulate synaptic weights in a neural network. Readers will benefit from state-of-the-art summaries of resistive synaptic devices, from the individual cell characteristics to the large-scale array integration. This book also discusses peripheral neuron circuits design challenges and design strategies. Finally, the authors describe the impact of device non-ideal properties (e.g. noise, variation, yield) and their impact on the learning performance at the system-level, using a device-algorithm co-design methodology.

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