Highly parallel and ultra-low-power probabilistic reasoning with programmable gaussian-like memory transistors
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Changhyeon | - |
dc.contributor.author | Rahimifard, Leila | - |
dc.contributor.author | Choi, Junhwan | - |
dc.contributor.author | Park, Jeong-ik | - |
dc.contributor.author | Lee, Chungryeol | - |
dc.contributor.author | Kumar, Divake | - |
dc.contributor.author | Shukla, Priyesh | - |
dc.contributor.author | Lee, Seung Min | - |
dc.contributor.author | Trivedi, Amit Ranjan | - |
dc.contributor.author | Yoo, Hocheon | - |
dc.contributor.author | Im, Sung Gap | - |
dc.date.accessioned | 2024-04-20T08:30:19Z | - |
dc.date.available | 2024-04-20T08:30:19Z | - |
dc.date.issued | 2024-03 | - |
dc.identifier.issn | 2041-1723 | - |
dc.identifier.issn | 2041-1723 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/90998 | - |
dc.description.abstract | Probabilistic inference in data-driven models is promising for predicting outputs and associated confidence levels, alleviating risks arising from overconfidence. However, implementing complex computations with minimal devices still remains challenging. Here, utilizing a heterojunction of p- and n-type semiconductors coupled with separate floating-gate configuration, a Gaussian-like memory transistor is proposed, where a programmable Gaussian-like current-voltage response is achieved within a single device. A separate floating-gate structure allows for exquisite control of the Gaussian-like current output to a significant extent through simple programming, with an over 10000 s retention performance and mechanical flexibility. This enables physical evaluation of complex distribution functions with the simplified circuit design and higher parallelism. Successful implementation for localization and obstacle avoidance tasks is demonstrated using Gaussian-like curves produced from Gaussian-like memory transistor. With its ultralow-power consumption, simplified design, and programmable Gaussian-like outputs, our 3-terminal Gaussian-like memory transistor holds potential as a hardware platform for probabilistic inference computing. Probabilistic inference hardware prevents overconfidence. Lee et al. report a Gaussian-like memory transistor using p-n junction coupled with separate floating gate, offering precise control of the Gaussian outputs, simplified circuit design, and low power consumption for inference computing. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | NATURE PORTFOLIO | - |
dc.title | Highly parallel and ultra-low-power probabilistic reasoning with programmable gaussian-like memory transistors | - |
dc.type | Article | - |
dc.identifier.wosid | 001187425700036 | - |
dc.identifier.doi | 10.1038/s41467-024-46681-2 | - |
dc.identifier.bibliographicCitation | NATURE COMMUNICATIONS, v.15, no.1 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.scopusid | 2-s2.0-85188064380 | - |
dc.citation.title | NATURE COMMUNICATIONS | - |
dc.citation.volume | 15 | - |
dc.citation.number | 1 | - |
dc.type.docType | Article | - |
dc.publisher.location | 독일 | - |
dc.subject.keywordPlus | IMAGE RECOGNITION | - |
dc.subject.keywordPlus | DIELECTRICS | - |
dc.subject.keywordPlus | CIRCUITS | - |
dc.subject.keywordPlus | DESIGN | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalWebOfScienceCategory | Multidisciplinary Sciences | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114
COPYRIGHT 2020 Gachon University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.