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• W4313462923 abstract "We propose electro-optical synaptic devices using surface-stabilized ferroelectric liquid crystals. Typical synaptic characteristics were observed for varying pulse time intervals, numbers of pulses, and signal voltages. Plasticity only occurred when pulses were applied at intervals shorter than the response time of the ferroelectric liquid crystal. Moreover, the plasticity increased with a higher pulse voltage and number of pulses. This demonstrates the importance of repeated learning. The synaptic weights required to make connections through learning in an artificial neural network can be determined by tuning the pulse signal. We discuss the high-speed computational potential of optical neuromorphic devices using liquid crystals." @default.
• W4313462923 created "2023-01-06" @default.
• W4313462923 creator A5051254369 @default.
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• W4313462923 date "2023-01-23" @default.
• W4313462923 modified "2023-10-17" @default.
• W4313462923 title "Electro-optical synaptic characteristics of ferroelectric liquid crystals for artificial intelligence" @default.
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• W4313462923 doi "https://doi.org/10.1364/ao.478415" @default.
• W4313462923 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36821144" @default.
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