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All Stochastic-Spiking Neural Network (AS-SNN): Noise Induced Spike Pulse Generator for Input and Output Neurons With Resistive Synaptic Array

Authors
Kim, HongguAn, YerimKim, MinchulHeo, Gyeong-ChanShim, Yong
Issue Date
Jan-2025
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Neurons; Noise; Codes; Calibration; Voltage; Stochastic processes; Hardware; Operational amplifiers; Synapses; Resistance; Spiking neural network; neuromorphic system; stochastic neuron
Citation
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, v.72, no.1, pp 78 - 82
Pages
5
Journal Title
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
Volume
72
Number
1
Start Page
78
End Page
82
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/79164
DOI
10.1109/TCSII.2024.3485178
ISSN
1549-7747
1558-3791
Abstract
Spiking neural network (SNN) based mixed-signal neuromorphic hardware gives high benefit in terms of speed and energy efficiency compared to conventional computing platform, thanks to its energy efficient data processing nature. However, on-chip realization of Poisson spike train to represent spike-encoded data has not yet fully achieved. Furthermore, the analog circuit components in mixed-signal neuromorphic hardwares are prone to variations which might lead to accuracy drop in SNN applications. In this brief, we demonstrated robust noise induced spike pulse generator for on-chip realization of Poisson spike train. The stochastic sigmoid neuron developed in our work exhibits better robustness than LIF neurons towards diverse RRAM device variation factors: 1) Random Telegraph Noise (RTN), 2) Stuck-At-Faults (SAFs) and 3) Endurance failures, guaranteeing robust SNN application.
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Shim, Yong
창의ICT공과대학 (전자전기공학부)
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