Cited 10 time in
Implementation of 8-bit reservoir computing through volatile ZrOx-based memristor as a physical reservoir
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ju, Dongyeol | - |
| dc.contributor.author | Koo, Minsuk | - |
| dc.contributor.author | Kim, Sungjun | - |
| dc.date.accessioned | 2024-08-13T06:30:18Z | - |
| dc.date.available | 2024-08-13T06:30:18Z | - |
| dc.date.issued | 2024-09 | - |
| dc.identifier.issn | 2211-2855 | - |
| dc.identifier.issn | 2211-3282 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/22860 | - |
| dc.description.abstract | In this study, we employed a sputtering process to construct a memristive device within the ITO/ZrOx/TaN structure for implementing neuromorphic computing. Initially, we scanned the basic electrical properties of the ITO/ZrOx/TaN device using a DC voltage sweep on the top ITO electrode. A highly uniform gradual resistive switching phenomenon was observed over 100 cycles. The current decay in the low-resistance state was effectively controlled by the volatile memory properties. Gradual conductance changes for potentiation and depression were achieved by applying electrical pulses, enabling the establishment of multi-level conductance states. In addition, the emulation of various synaptic functions was achieved by following the learning rules of SRDP, EPSC, STDP, ADSP, Pavlovian associative learning, and PPF. Finally, 8-bit reservoir computing was demonstrated in cost-effective pattern generation and recognition, highlighting the ITO/ZrOx/TaN device's advantageous memory storage properties for synaptic characteristics. © 2024 Elsevier Ltd | - |
| dc.format.extent | 13 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | Elsevier BV | - |
| dc.title | Implementation of 8-bit reservoir computing through volatile ZrOx-based memristor as a physical reservoir | - |
| dc.type | Article | - |
| dc.publisher.location | 네델란드 | - |
| dc.identifier.doi | 10.1016/j.nanoen.2024.109958 | - |
| dc.identifier.scopusid | 2-s2.0-85198002511 | - |
| dc.identifier.wosid | 001362110900001 | - |
| dc.identifier.bibliographicCitation | Nano Energy, v.128, pp 1 - 13 | - |
| dc.citation.title | Nano Energy | - |
| dc.citation.volume | 128 | - |
| dc.citation.startPage | 1 | - |
| dc.citation.endPage | 13 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scie | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.relation.journalResearchArea | Chemistry | - |
| dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
| dc.relation.journalResearchArea | Materials Science | - |
| dc.relation.journalResearchArea | Physics | - |
| dc.relation.journalWebOfScienceCategory | Chemistry, Physical | - |
| dc.relation.journalWebOfScienceCategory | Nanoscience & Nanotechnology | - |
| dc.relation.journalWebOfScienceCategory | Materials Science, Multidisciplinary | - |
| dc.relation.journalWebOfScienceCategory | Physics, Applied | - |
| dc.subject.keywordPlus | RESISTIVE SWITCHING CHARACTERISTICS | - |
| dc.subject.keywordPlus | FILMS | - |
| dc.subject.keywordPlus | OXIDE | - |
| dc.subject.keywordAuthor | Artificial synapse | - |
| dc.subject.keywordAuthor | High bit reservoir computing | - |
| dc.subject.keywordAuthor | Neuromorphic system | - |
| dc.subject.keywordAuthor | Resistive switching device | - |
| dc.subject.keywordAuthor | ZrO<sub>x</sub> | - |
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