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dc.contributor.advisorHalverson, Don R.en_US
dc.creatorBhagawat, Pankajen_US
dc.date.accessioned2004-09-30T01:42:27Z
dc.date.available2004-09-30T01:42:27Z
dc.date.created2003-08en_US
dc.date.issued2004-09-30
dc.identifier.urihttp://hdl.handle.net/1969.1/107
dc.description.abstractIn this work we have made use of a geometric approach which quantifies robustness and performance and we finally combine them using a cost function. In particular, we calculate the robustness of the estimate of standard deviation of nominally Laplacian distribution. As this distribution is imperfectly known, we employ a more general family, the generalized Gaussian; Laplacian distribution, is one of the members of this family. We compute parameter estimates and present a classical algorithm which is then analyzed for distribution from the generalized Gaussian family. We calculate the mean squared error according to the censoring height k. We measure performance as a function of (1/MSE) and combine it with robustness using a cost criterion and design a robust estimator which optimizes a mix of performance and robustness specified by the user.en_US
dc.format.extent827488 bytes
dc.format.extent63481 bytes
dc.format.mediumelectronicen_US
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_USen_US
dc.publisherTexas A&M Universityen_US
dc.subjectPerformanceen_US
dc.subjectRobustnessen_US
dc.subjectcost functionen_US
dc.titleDesign of a robust parameter estimator for nominally Laplacian noiseen_US
dc.typeBooken
dc.typeThesisen
thesis.degree.departmentElectrical Engineeringen_US
thesis.degree.disciplineElectrical Engineeringen_US
thesis.degree.grantorTexas A&M Universityen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelMastersen_US
dc.contributor.committeeMemberGeorghiades, Costas N.en_US
dc.contributor.committeeMemberChang, Kaien_US
dc.contributor.committeeMemberFriesen, Donalden_US
dc.type.genreElectronic Thesisen_US
dc.type.materialtexten_US
dc.format.digitalOriginborn digitalen_US


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