Binary Electronic Synapses for Integrating Digital and Neuromorphic Computation in a Single Physical Platform
- Authors
- Wu, Chaoxing; Zhang, Yongai; Zhou, Xiongtu; Li, Dianlun; Park, Jae Hyeon; An, Haoqun; Sung, Sihyun; Lin, Jintang; Guo, Tailiang; Li, Fushan; Kim, Tae Whan
- Issue Date
- Apr-2020
- Publisher
- AMER CHEMICAL SOC
- Keywords
- binary electronic synapse; memristive device; digital computation; neuromorphic computation; cation drift
- Citation
- ACS APPLIED MATERIALS & INTERFACES, v.12, no.14, pp.17130 - 17138
- Indexed
- SCIE
SCOPUS
- Journal Title
- ACS APPLIED MATERIALS & INTERFACES
- Volume
- 12
- Number
- 14
- Start Page
- 17130
- End Page
- 17138
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/9932
- DOI
- 10.1021/acsami.0c02145
- ISSN
- 1944-8244
- Abstract
- As a promising advanced computation technology, the integration of digital computation with neuromorphic computation into a single physical platform holds the advantage of a precise, deterministic, fast data process as well as the advantage of a flexible, paralleled, fault-tolerant data process. Even though two-terminal memristive devices have been respectively proved as leading electronic elements for digital computation and neuromorphic computation, it is difficult to steadily maintain both sudden-state-change and gradual-state-change in a single device due to the entirely different operating mechanisms. In this work, we developed a digital-analog compatible memristive device, namely, binary electronic synapse, through realizing controllable cation drift in a memristive layer. The devices feature nonvolatile binary memory as well as artificial neuromorphic plasticity with high operation endurance. With strong nonlinearity in switching dynamics, binary switching, neuromorphic plasticity, two-dimension information store, and trainable memory can be implemented by a single device.
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