Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/5614
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dc.contributor.authorAgrawal, Rajanen_US
dc.contributor.authorMukherjee, Shaibalen_US
dc.date.accessioned2022-03-17T01:00:00Z-
dc.date.accessioned2022-03-17T15:42:51Z-
dc.date.available2022-03-17T01:00:00Z-
dc.date.available2022-03-17T15:42:51Z-
dc.date.issued2020-
dc.identifier.citationKumar, S., Agrawal, R., Das, M., Kumar, P., & Mukherjee, S. (2020). Analytical modeling of a Y2O3-based memristive system for synaptic applications. Journal of Physics D: Applied Physics, 53(30) doi:10.1088/1361-6463/ab810een_US
dc.identifier.issn0022-3727-
dc.identifier.otherEID(2-s2.0-85086597899)-
dc.identifier.urihttps://doi.org/10.1088/1361-6463/ab810e-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/5614-
dc.description.abstractHere, an analytical model for Y2O3-based memristive systems is presented, since a traditional model such as the Yakopcic model significantly deviates to capture the neuromorphic behavior for yttria-based memristive systems. On the one hand, the proposed model has high correlation with the reported experimental data and overcomes the shortcomings of the Yakopcic model in the form of a lack of non-linear behavior in the drift current at the device boundaries by introducing a new window function and state variable. On the other hand, the Yakopcic model depends upon the device threshold voltage parameters, while the proposed model is generic and remains independent of any pre-defined set of threshold voltage parameters. As a result, the proposed analytical model can be used in designing real-world applications based on the neuromorphic properties of yttria-based or any generic memristive systems. © 2020 IOP Publishing Ltd.en_US
dc.language.isoenen_US
dc.publisherInstitute of Physics Publishingen_US
dc.sourceJournal of Physics D: Applied Physicsen_US
dc.subjectMemristorsen_US
dc.subjectThreshold voltageen_US
dc.subjectYttrium oxideen_US
dc.subjectDrift currentsen_US
dc.subjectMemristive systemsen_US
dc.subjectNeuromorphicen_US
dc.subjectNonlinear behavioren_US
dc.subjectState variablesen_US
dc.subjectTraditional modelsen_US
dc.subjectVoltage parametersen_US
dc.subjectWindow functionsen_US
dc.subjectAnalytical modelsen_US
dc.titleAnalytical modeling of a Y2O3-based memristive system for synaptic applicationsen_US
dc.typeJournal Articleen_US
Appears in Collections:Department of Electrical Engineering

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