Neuro-inspired Computing Using Resistive Synaptic Devices
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Beschreibung
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.
• Provides single-source reference to recent breakthroughs in resistive synaptic devices, not only at individual cell-level, but also at integrated array-level;• Includes detailed discussion of the peripheral circuits and array architecture design of the neuro-crossbar system;• Focuses on new experimental results that are likely to solve practical, artificial intelligent problems, such as image classification.
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.
Provides single-source reference to recent breakthroughs in resistive synaptic devices, not only at individual cell-level, but also at integrated array-level Includes detailed discussion of the peripheral circuits and array architecture design of the neuro-crossbar system Focuses on new experimental results that are likely to solve practical, artificial intelligent problems, such as image classification
Autor*in
Shimeng Yu
Themen in »Neuro-inspired Computing Using Resistive Synaptic Devices«
neuro-inspired computing resistive synaptic devices Phase change memory peripheral neuron circuits design memristors