首页|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)
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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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.”
IncheonSouth KoreaAsiaEngineeringElectronicsNetworksNeural NetworksRandom Access Memory Incheon National University
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