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A Quantized-Weight-Splitting Method of RRAM Arrays for Neuromorphic Applications

In asynchronous Spiking Neural Networks (SNNs), the voltage division between passive resistive random-access memory (RRAM) arrays and neuron circuits presents a significant challenge, affecting the overall network accuracy and power efficiency. This study introduces the quantized-weight-splitting me...

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Principais autores: Kyungchul Park, Sungjoon Kim, Jong-Hyuk Park, Woo Young Choi
פורמט: Artigo
שפה:Inglês
יצא לאור: IEEE 2024-01-01
סדרה:IEEE Access
נושאים:
Low power
neuromorphic applications
RRAM
spiking neural networks
two-terminal devices
weight distortion
גישה מקוונת:https://ieeexplore.ieee.org/document/10508959/
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