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Device‐Algorithm Co‐Optimization for an On‐Chip Trainable Capacitor‐Based Synaptic Device with IGZO TFT and Retention‐Centric Tiki‐Taka Algorithm
Analog in‐memory computing synaptic devices are widely studied for efficient implementation of deep learning. However, synaptic devices based on resistive memory have difficulties implementing on‐chip training due to the lack of means to control the amount of resistance change and large device varia...
Autores principales: | Won, Jongun, Kang, Jaehyeon, Hong, Sangjun, Han, Narae, Kang, Minseung, Park, Yeaji, Roh, Youngchae, Seo, Hyeong Jun, Joe, Changhoon, Cho, Ung, Kang, Minil, Um, Minseong, Lee, Kwang‐Hee, Yang, Jee‐Eun, Jung, Moonil, Lee, Hyung‐Min, Oh, Saeroonter, Kim, Sangwook, Kim, Sangbum |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582414/ https://www.ncbi.nlm.nih.gov/pubmed/37559176 http://dx.doi.org/10.1002/advs.202303018 |
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