DocumentCode
3603715
Title
A CMOS Spiking Neuron for Brain-Inspired Neural Networks With Resistive Synapses and In Situ Learning
Author
Xinyu Wu ; Saxena, Vishal ; Kehan Zhu ; Balagopal, Sakkarapani
Author_Institution
Dept. of Electr. & Comput. Eng., Boise State Univ., Boise, ID, USA
Volume
62
Issue
11
fYear
2015
Firstpage
1088
Lastpage
1092
Abstract
Nanoscale resistive memory devices are expected to fuel dense integration of electronic synapses for large-scale neuromorphic systems. To realize such a brain-inspired computing chip, a compact CMOS spiking neuron that performs in situ learning and computing while driving a large number of resistive synapses is desired. This brief presents a novel leaky integrate-and-fire neuron design that implements the dual-mode operation of current integration and synaptic drive, with a single operational amplifier (opamp) and enables in situ learning with crossbar resistive synapses. The proposed design was implemented in a 0.18-μm CMOS technology. Measurements show neuron´s ability to drive a thousand resistive synapses and demonstrate in situ associative learning. The neuron circuit occupies a small area of 0.01 mm2 and has an energy efficiency value of 9.3 pJ/spike/synapse.
Keywords
CMOS integrated circuits; brain; energy conservation; neural nets; operational amplifiers; brain-inspired computing chip; brain-inspired neural networks; compact CMOS spiking neuron; crossbar resistive synapses; current integration; dual-mode operation; electronic synapses; energy efficiency; fuel dense integration; in situ learning; large-scale neuromorphic systems; leaky integrate-and-fire neuron design; nanoscale resistive memory devices; operational amplifier; size 0.18 mum; synaptic drive; thousand resistive synapses; CMOS integrated circuits; Electric potential; Fires; Firing; Neuromorphics; Neurons; Machine Learning; Machine learning; Neuromorphic; Resistive Memory; Silicon Neuron; Spiking Neural Networks; neuromorphic; resistive memory; silicon neuron; spiking neural networks;
fLanguage
English
Journal_Title
Circuits and Systems II: Express Briefs, IEEE Transactions on
Publisher
ieee
ISSN
1549-7747
Type
jour
DOI
10.1109/TCSII.2015.2456372
Filename
7156114
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