Optogenetics inspired transition metal dichalcogenide neuristors for in-memory deep recurrent neural networks

Optogenetics inspired transition metal dichalcogenide neuristors for in-memory deep recurrent neural networks

Accomplishing complex cognitive tasks such as speech recognition calls for artificial intelligence hardware with high computing precision. John et al. propose deep recurrent neural networks based on optoelectronic transition metal dichalcogenide memristors with high weight precision for in-memory co...

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Autores principales: Rohit Abraham John, Jyotibdha Acharya, Chao Zhu, Abhijith Surendran, Sumon Kumar Bose, Apoorva Chaturvedi, Nidhi Tiwari, Yang Gao, Yongmin He, Keke K. Zhang, Manzhang Xu, Wei Lin Leong, Zheng Liu, Arindam Basu, Nripan Mathews
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
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Acceso en línea:https://doaj.org/article/6c1806d8270d4d5db127aa7ebd08d4ee
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