An advanced neuromorphic accelerator on FPGA for next-G spectrum sensing

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dc.contributor.authorAzmine, Muhammad Farhanen
dc.contributor.committeechairYi, Yangen
dc.contributor.committeememberHa, Dongen
dc.contributor.committeememberJones, Creed F. IIIen
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2024-05-21T14:55:34Zen
dc.date.available2024-05-21T14:55:34Zen
dc.date.issued2024-04-10en
dc.description.abstractIn modern communication systems, it’s important to detect and use available radio frequencies effectively. However, current methods face challenges with complexity and noise interference. We’ve developed a new approach using advanced artificial intelligence (AI) based computing techniques to improve efficiency and accuracy in this process. Our method shows promising results, requiring only minimal additional resources in exchange of improved performance compared to older techniques.en
dc.description.abstractgeneralIn modern communication systems, it’s important to detect and use available radio frequencies effectively. However, current methods face challenges with complexity and noise interference. We’ve developed a new approach using advanced artificial intelligence (AI) based computing techniques to improve efficiency and accuracy in this process. Our method shows promising results, requiring only minimal additional resources in exchange of improved performance compared to older techniques.en
dc.description.degreeMaster of Scienceen
dc.format.mediumETDen
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttps://hdl.handle.net/10919/119039en
dc.language.isoenen
dc.publisherVirginia Techen
dc.rightsCreative Commons Attribution-NoDerivatives 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/en
dc.subjectField Programmable Gate Arrayen
dc.subjectHardware acceleratoren
dc.subjectOn-Chip learningen
dc.subjectArtificial intelligenceen
dc.subjectRecurrent Neural Networken
dc.subjectSpike-Time-Dependent-Plasticityen
dc.subjectCognitive-Radio-Networken
dc.subjectSpectrum Sensingen
dc.titleAn advanced neuromorphic accelerator on FPGA for next-G spectrum sensingen
dc.typeThesisen
thesis.degree.disciplineComputer Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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