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dc.contributor.advisorMercer, M. Ray
dc.creatorTrinka, Michael Robert
dc.date.accessioned2004-09-30T01:42:04Z
dc.date.available2004-09-30T01:42:04Z
dc.date.created2003-08
dc.date.issued2004-09-30
dc.identifier.urihttps://hdl.handle.net/1969.1/95
dc.description.abstractGood failure analysis is the ability to determine the site of a circuit defect quickly and accurately. We propose a method for defect site prediction that is based on a site's probability of excitation, making no assumptions about the type of defect being analyzed. We do this by analyzing fault signatures and comparing them to the defect signature. We use this information to construct an ordered list of sites that are likely to be the site of the defect.en
dc.format.extent213991 bytesen
dc.format.extent32875 bytesen
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherTexas A&M University
dc.subjectdefecten
dc.subjecttestingen
dc.subjectcircuiten
dc.subjectfaulten
dc.subjectdiagnosisen
dc.titleDefect site prediction based upon statistical analysis of fault signaturesen
dc.typeBooken
dc.typeThesisen
thesis.degree.departmentElectrical Engineeringen
thesis.degree.disciplineComputer Engineeringen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelMastersen
dc.contributor.committeeMemberReddy, A. L. Narasimha
dc.contributor.committeeMemberChilds, S. Bart
dc.type.genreElectronic Thesisen
dc.type.materialtexten
dc.format.digitalOriginborn digitalen


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