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FUZYE: A Fuzzy C-Means Analog IC Yield Optimization using Evolutionary-based Algorithms

2020-01Journal article Restricted access
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dc.contributor.authorCanelas, António
dc.contributor.authorPóvoa, Ricardo
dc.contributor.authorMartins, Ricardo
dc.contributor.authorLourenço, Nuno
dc.contributor.authorGuilherme, Jorge
dc.contributor.authorCarvalho, João Paulo
dc.contributor.authorHorta, Nuno
dc.date.accessioned2025-05-08T16:14:37Z
dc.date.available2025-05-08T16:14:37Z
dc.date.issued2020-01
dc.description.abstractThis paper presents fuzzy c-means-based yield estimation (FUZYE), a methodology that reduces the time impact caused by Monte Carlo (MC) simulations in the context of analog integrated circuits (ICs) yield estimation, enabling it for yield optimization with population-based algorithms, e.g., the genetic algorithm (GA). MC analysis is the most general and reliable technique for yield estimation, yet the considerable amount of time it requires has discouraged its adoption in population-based optimization tools. The proposed methodology reduces the total number of MC simulations that are required, since, at each GA generation, the population is clustered using a fuzzy c-means (FCMs) technique, and, only the representative individual (RI) from each cluster is subject to MC simulations. This paper shows that the yield for the rest of the population can be estimated based on the membership degree of FCM and RIs yield values alone. This new method was applied on two real circuit-sizing optimization problems and the obtained results were compared to the exhaustive approach, where all individuals of the population are subject to MC analysis. The FCM approach presents a reduction of 89% in the total number of MC simulations, when compared to the exhaustive MC analysis over the full population. Moreover, a k-means-based clustering algorithm was also tested and compared with the proposed FUZYE, with the latest showing an improvement up to 13% in yield estimation accuracyeng
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationA. Canelas et al., "FUZYE: A Fuzzy c-Means Analog IC Yield Optimization Using Evolutionary-Based Algorithms," in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
dc.identifier.doi10.1109/TCAD.2018.2883978
dc.identifier.issn1937-4151
dc.identifier.urihttp://hdl.handle.net/10400.26/57796
dc.language.isoengpt_PT
dc.peerreviewedyes
dc.publisherIEEEpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectOptimization
dc.subjectIntegrated circuit modeling
dc.subjectYield estimation
dc.subjectSociology
dc.subjectStatistics
dc.subjectAnalytical models
dc.titleFUZYE: A Fuzzy C-Means Analog IC Yield Optimization using Evolutionary-based Algorithmspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage13pt_PT
oaire.citation.issue1pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleIEEE Transactions on Computer-Aided Design of Integrated Circuitspt_PT
oaire.citation.volume39pt_PT
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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