DC Field | Value | Language |
---|---|---|
dc.contributor.author | DONGWOOK, LEE | - |
dc.contributor.author | Lee, Jongwon | - |
dc.contributor.author | CHULJUN, LEE | - |
dc.contributor.author | KIM, SEYOUNG | - |
dc.contributor.author | Hwang, Hyunsang | - |
dc.date.accessioned | 2023-03-03T05:41:11Z | - |
dc.date.available | 2023-03-03T05:41:11Z | - |
dc.date.created | 2023-03-02 | - |
dc.date.issued | 2022-09 | - |
dc.identifier.issn | 0018-9383 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/116595 | - |
dc.description.abstract | Neuromorphic computing has gained a considerable research interest due to its potential in realizing highly efficient parallel computations. However, the existing neuromorphic architectures face various drawbacks. In this study, we present an integrate-and-fire (I&F) neuron using a Li-based electrochemical random access memory (Li-ECRAM) to achieve exceptional area efficiency and low-power neuromorphic computing. The proposed Li-ECRAM neuron employs a significantly reduced number of transistors when compared to other novel nonvolatile memory-based I&F neurons due to linear current integration characteristics and a high linear conductance response to the input current. As the integration-type Li-ECRAM is linear, it eliminates the requirement of a nonlinear compensating circuit. Therefore, a Li-ECRAM-based neuron has a simple structure comprising Li-ECRAM, reset transistor, inverter, and pulse generator. Furthermore, we also evaluate the operation speed and energy consumption of the proposed neuron, demonstrating the potential for high-speed and low-power operation. The proposed neuron can be applied in large-scale neuromorphic hardware applications due to the scalability and low energy consumption of Li-ECRAM. IEEE | - |
dc.language | English | - |
dc.publisher | Institute of Electrical and Electronics Engineers | - |
dc.relation.isPartOf | IEEE Transactions on Electron Devices | - |
dc.title | Integrate-and-Fire Neuron With Li-Based Electrochemical Random Access Memory Using Native Linear Current Integration Characteristics | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/ted.2022.3188241 | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | IEEE Transactions on Electron Devices, v.69, no.9, pp.4889 - 4893 | - |
dc.identifier.wosid | 000826071600001 | - |
dc.citation.endPage | 4893 | - |
dc.citation.number | 9 | - |
dc.citation.startPage | 4889 | - |
dc.citation.title | IEEE Transactions on Electron Devices | - |
dc.citation.volume | 69 | - |
dc.contributor.affiliatedAuthor | DONGWOOK, LEE | - |
dc.contributor.affiliatedAuthor | Lee, Jongwon | - |
dc.contributor.affiliatedAuthor | CHULJUN, LEE | - |
dc.contributor.affiliatedAuthor | KIM, SEYOUNG | - |
dc.contributor.affiliatedAuthor | Hwang, Hyunsang | - |
dc.identifier.scopusid | 2-s2.0-85134263507 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | Electrochemical random access memory (ECRAM) | - |
dc.subject.keywordAuthor | integrate-and-fire (I&F) neuron | - |
dc.subject.keywordAuthor | Logic gates | - |
dc.subject.keywordAuthor | Membrane potentials | - |
dc.subject.keywordAuthor | neuromorphic | - |
dc.subject.keywordAuthor | Neurons | - |
dc.subject.keywordAuthor | Nonvolatile memory | - |
dc.subject.keywordAuthor | Random access memory | - |
dc.subject.keywordAuthor | Transistors | - |
dc.subject.keywordAuthor | Voltage | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Physics, Applied | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Physics | - |
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