Towards autonomous FDIR: machine learning for identification of point and contextual anomalies onboard a satellite

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dc.contributor.authorPraveen, M. V. Ramachandra
dc.date.accessioned2026-09-24T07:49:31Z
dc.date.issued2024-10
dc.descriptionThesis submitted in partial fulfillment of the requirements for the award of the Degree of Doctor of Philosophy (Electronics & Communication Engineering)
dc.identifier.citationUnder the guidance of Dr. Piyush Kuchhal, Professor, UPES & Dr. Sushabhan Choudhury, Professor, UPES
dc.identifier.urihttps://dr.ddn.upes.ac.in/handle/123456789/4584
dc.language.isoen
dc.publisherSchool of Advanced Engineering, UPES, Dehradun
dc.subjectThesis
dc.subjectElectronics and Communication Engineering
dc.subjectElectronics Engineering
dc.subjectSatellite Proliferation
dc.subjectArtificial Intelligence
dc.subjectMachine Learning Models
dc.titleTowards autonomous FDIR: machine learning for identification of point and contextual anomalies onboard a satellite
dc.typeThesis

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