Analog memristive synapse based on topotactic phase transition for high-performance neuromorphic computing and neural network pruning-Reference-Cited by-同舟云学术

Analog memristive synapse based on topotactic phase transition for high-performance neuromorphic computing and neural network pruning

Published:2021-07-16 Issue:29 Volume:7 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Mou Xing¹^ORCID,Tang Jianshi¹²^ORCID,Lyu Yingjie³,Zhang Qingtian²^ORCID,Yang Siyao¹,Xu Feng¹^ORCID,Liu Wei¹,Xu Minghong¹,Zhou Yu³^ORCID,Sun Wen¹,Zhong Yanan¹,Gao Bin¹²^ORCID,Yu Pu²³^ORCID,Qian He¹²,Wu Huaqiang¹²^ORCID

Affiliation:

1. School of Integrated Circuits, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.

2. Beijing Innovation Center for Future Chips (ICFC), Tsinghua University, Beijing, China.

3. State Key Laboratory of Low-Dimensional Quantum Physics and Department of Physics, Tsinghua University, Beijing 100084, China.

Abstract

Memristor with topotactic phase transition demonstrates controllable analog switching and implements neural network pruning.

Funder

National Natural Science Foundation of China

National Basic Research Program of China

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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