Compensated Current Mirror Neuron Circuits for Linear Charge Integration with Ultralow Static Power in Spiking Neural Networks

Spiking Neural Networks In article number 2400673, Jonghyuk Park, Sungjoon Kim, and Woo Young Choi present a neuron circuit that optimizes vector-matrix multiplication performance in spiking neural networks (SNNs) while ensuring low-power consumption. This research validates the achievement of high SNN system accuracy through a CMOS neuron circuit arranged to prevent non-linear operations that occur during the integration of massive synaptic arrays and neurons.

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Publication Details

Journal
Advanced Intelligent Systems
Published
2025-02-01
DOI
https://doi.org/10.1002/aisy.202570010
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

Compensated Current Mirror Neuron Circuits for Linear Charge Integration with Ultralow Static Power in Spiking Neural Networks

Woo Young Choi, Jong-Hyuk Park, Sungjoon Kim
Advanced Intelligent Systems
Advanced Memory and Neural Computing
article

Compensated Current Mirror Neuron Circuits for Linear Charge Integration with Ultralow Static Power in Spiking Neural Networks

Woo Young Choi, Jong-Hyuk Park, Sungjoon Kim
article en

Abstract

Spiking Neural Networks In article number 2400673, Jonghyuk Park, Sungjoon Kim, and Woo Young Choi present a neuron circuit that optimizes vector-matrix multiplication performance in spiking neural networks (SNNs) while ensuring low-power consumption. This research validates the achievement of high SNN system accuracy through a CMOS neuron circuit arranged to prevent non-linear operations that occur during the integration of massive synaptic arrays and neurons.

Advanced Intelligent SystemsVol. 7(2)
Seoul National University (KR)
Affordable and clean energy
Openalex Percentile: Top 98%
Advanced Memory and Neural Computing
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