Neuro-inspired Computing Using Resistive Synaptic Devices

by Shimeng Yu (Editor)

Introduction to Neuro-Inspired Computing using Resistive Synaptic Devices.- Part Device-level Demonstrations of Resistive Synaptic Devices.- Phase Change Memory based Synaptic Devices.- Pr0.7Ca0.3MnO3 (PCMO) based Synaptic Devices.- TaOx/TiO2 based Synaptic Devices.- Part Array-level Demonstrations of Resistive Synaptic Devices and Neural Networks.- Training and Inference in Hopfield Network using 10×10 Phase Change Synaptic Array.- Experimental Demonstration of Firing-Rate Neural Networks based on Metal-Oxide Memristive Crossbars.- Weight Tuning of Resistive Synaptic Devices and Convolution Kernel Operation on 12×12 Cross-Point Array.- Spiking Neural Network with 256×256 PCM Array.- Part Circuit, Architecture and Algorithm-level Design of Resistive Synaptic Devices based Neuromorphic System.- Peripheral Circuit Design Considerations of Neuro-inspired Architectures.- Processing-in-Memory Architecture Design for Accelerating Neuro-Inspired Algorithms.- Multi-layer Perceptron Impact of Non-Ideal Conductance and Area-Efficient Peripheral Circuits.- Impact of Non-Ideal Resistive Synaptic Device Behaviors on Implementation of Sparse Coding Algorithm.- Binary OxRAM/CBRAM Memories for Efficient Implementations of Embedded Neuromorphic Circuits.

284 pages, Paperback

Published April 27, 2017