Controllable digital resistive switching for artificial synapses and pavlovian learning algorithm.

Kumar, Mohit; Abbas, Sohail; Lee, Jung-Ho; Kim, Joondong

Kumar, Mohit; Abbas, Sohail; Lee, Jung-Ho; Kim, Joondong.

Afiliação

Kumar M; Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon, 22012, Republic of Korea and Department of Electrical Engineering, Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea. joonkim@incheon.a
Abbas S; Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon, 22012, Republic of Korea and Department of Electrical Engineering, Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea. joonkim@incheon.a
Lee JH; Department of Materials and Chemical Engineering, Hanyang University, Ansan, Kyunggido 15588, Korea. jungho@hanyang.ac.kr.
Kim J; Photoelectric and Energy Device Application Lab (PEDAL), Multidisciplinary Core Institute for Future Energies (MCIFE), Incheon, 22012, Republic of Korea and Department of Electrical Engineering, Incheon National University, 119 Academy Rd. Yeonsu, Incheon, 22012, Republic of Korea. joonkim@incheon.a

Nanoscale ; 11(33): 15596-15604, 2019 Sep 07.

Article em En | MEDLINE | ID: mdl-31403638

Assuntos

Algoritmos; Eletricidade; Nanofios/química; Silício/química; Prata/química; Sinapses/fisiologia; Óxido de Zinco/química

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos Tipo de estudo: Prognostic_studies Idioma: En Revista: Nanoscale Ano de publicação: 2019 Tipo de documento: Article País de publicação: Reino Unido

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