Multimode Synaptic Operation of a HfAlOx-Based Memristor as a Metaplastic Device for Neuromorphic Applications Multimode Synaptic Operation of a HfAlOx-Based Memristor as a Metaplastic Device for Neuromorphic Applications AITranslate
Abstract AITranslate
Metaplasticity is one of the synaptic functions in the brain, known as the plasticity of synapse plasticity. It allows some specific functions of the brain, such as continual learning, rapid homeostasis, and synaptic tag-and-capture functions. Here, we propose an electrically triggerable HfAlOx-based metaplastic device that exhibits reversible multimode synaptic behaviors. The origin of the synaptic characteristic change is the change in the serial and parallel resistance components of the memristive system, accompanied by unbalanced oxygen flux during the set and reset switching, triggered by the priming activity. Four distinguishable potentiation and depression characteristics (two stable modes and two transition modes) are suggested, which can be explained using a plausible schematic model. A hardware-based adaptive learning system for artificial neural networks is proposed as a potential application of the metaplastic device.
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DOI:https://doi.org/10.1021/acsaelm.2c00320
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Metaplasticity is one of the synaptic functions in the brain, known as the plasticity of synapse plasticity. It allows some specific functions of the brain, such as continual learning, rapid homeostasis, and synaptic tag-and-capture functions. Here, we propose an electrically triggerable HfAlOx-based metaplastic device that exhibits reversible multimode synaptic behaviors. The origin of the synaptic characteristic change is the change in the serial and parallel resistance components of the memristive system, accompanied by unbalanced oxygen flux during the set and reset switching, triggered by the priming activity. Four distinguishable potentiation and depression characteristics (two stable modes and two transition modes) are suggested, which can be explained using a plausible schematic model. A hardware-based adaptive learning system for artificial neural networks is proposed as a potential application of the metaplastic device.
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| GB/T 7714-2015 | [1] Hyung Seok Shin, Hanchan Song, Do Hoon Kim, et al. ACS Applied Electronic Materials, 2022(4). DOI:10.1021/acsaelm.2c00320. |
| MLA | [1] Hyung Seok Shin, et al., ACS Applied Electronic Materials, no. 4, 2022, https://doi.org/10.1021/acsaelm.2c00320. |
| APA | [1] Hyung Seok Shin, Hanchan Song, Do Hoon Kim, Alba Martinez, Woon Hyung Cheong, & Kyung Min Kim. (2022). ACS Applied Electronic Materials(4). https://doi.org/10.1021/acsaelm.2c00320 |
| IEEE | [1] Hyung Seok Shin, Hanchan Song, Do Hoon Kim, Alba Martinez, Woon Hyung Cheong, and Kyung Min Kim, ACS Applied Electronic Materials, no. 4, 2022, doi: 10.1021/acsaelm.2c00320. keywords: {HfAlOx resistive switching memristor metaplasticity neuromorphic} |
