New Engineering Findings from Incheon National University Discussed (Multibit, Lead-free Cs2sni6 Resistive Random Access Memory With Self-compliance for Improved Accuracy In Binary Neural Network Application)

Robotics & Machine Learning Daily News2024，Issue(Jan.25) ：10-10.

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New Engineering Findings from Incheon National University Discussed (Multibit, Lead-free Cs2sni6 Resistive Random Access Memory With Self-compliance for Improved Accuracy In Binary Neural Network Application)

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Abstract

By a News Reporter-Staff News Editor at Network Daily News - A new studyon Engineering is now available. According to news originating from Incheon, South Korea, by NewsRxcorrespondents, research stated, “In the realm of neuromorphic computing, integrating Binary NeuralNetworks (BNN) with non-volatile memory based on emerging materials can be a promising avenue forintroducing novel functionalities. This study underscores the viability of lead-free, air-stable Cs2SnI6 (CSI)based resistive random access memory (RRAM) devices as synaptic weights in neuromorphic architectures,specifically for BNNs applications.”

Key words

Incheon/South Korea/Asia/Engineering/Electronics/Networks/Neural Networks/Random Access Memory Incheon National University

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出版年

2024

Robotics & Machine Learning Daily News

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