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dc.contributor.advisorHo, Dominic K. C.eng
dc.contributor.authorOddiraju, Swetha, 1981-eng
dc.date.issued2007eng
dc.date.submitted2007 Summereng
dc.descriptionThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.eng
dc.descriptionTitle from title screen of research.pdf file (viewed on September 29, 2008)eng
dc.descriptionIncludes bibliographical references.eng
dc.descriptionThesis (M.S.) University of Missouri-Columbia 2007.eng
dc.descriptionDissertations, Academic -- University of Missouri--Columbia -- Electrical engineering.eng
dc.description.abstract[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] Adaptive filtering is a common solution to many signal processing applications in which the environments are time varying. Its performance is limited by the misadjustment. A method to reduce the misadjustment when the additive noise in the desired signal is correlated is investigated in this work. The proposed method consists of two adaptive components: a modeling filter and a noise whitening filter. The proposed method performs better than the conventional LMS and RLS algorithms both in convergence speed and misadjustment factor. The performance of the adaptive filter when updated using LMS is observed. The improvement factor is proportional to the ratio of the noise power to white innovation power in the desired signal. The reduction in gradient noise allows larger step size, thus increasing the overall performance of the system. Both theoretical and simulation results proved that the proposed method gives a smaller misadjustment and better tracking capability than existing methods.eng
dc.identifier.merlinb64879422eng
dc.identifier.oclc259225096eng
dc.identifier.urihttps://hdl.handle.net/10355/6271
dc.identifier.urihttps://doi.org/10.32469/10355/6271eng
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsAccess is limited to the campus of the University of Missouri--Columbia.eng
dc.subjectmodeling filter; noise whitening filter.eng
dc.subjectmodeling filter; noise whitening filtereng
dc.subject.lcshAdaptive filterseng
dc.subject.lcshSignal processingeng
dc.titleImproving performance for adaptive filtering with voice applicationseng
dc.typeThesiseng
thesis.degree.disciplineElectrical and computer engineering (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelMasterseng
thesis.degree.nameM.S.eng


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