Estimation of repetition rate from signal and texture features

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dc.contributor.advisorFigueiredo, Rui J. P. deen_US
dc.contributor.committeeMemberParks, Thomas W.en_US
dc.contributor.committeeMemberDufour, Reginald J.en_US
dc.creatorTagare, Hemant D.en_US
dc.date.accessioned2018-12-18T21:21:09Zen_US
dc.date.available2018-12-18T21:21:09Zen_US
dc.date.issued1983en_US
dc.description.abstractThis thesis develops relevant definitions and a theoretical basis for estimating the repetition rate of a random repetitive signal. The repetition rate is estimated by looking for repetition amongst local features of the signals. These features have to satisfy a uniqueness condition, and we have shown that the derivatives of a signal constitute a set of such features. The estimator has been shown to be asymptotically unbiased. The estimation algorithm can not only be tuned to the waveshape information of the signal (by a proper choice of features), but also to the extent of non-stationarity expected in the input signal class. A set of features has been obtained for applying this algorithm to repetitive textured images and voiced speech signals. Vith these features, it has been possible to extract the repetition rate in both the above classes of signals. In the case of voiced speech this rate corresponds to its pitch.en_US
dc.format.digitalOriginreformatted digitalen_US
dc.format.extent115 ppen_US
dc.identifier.callnoTHESIS E.E. 1983 TAGAREen_US
dc.identifier.citationTagare, Hemant D.. "Estimation of repetition rate from signal and texture features." (1983) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/104335">https://hdl.handle.net/1911/104335</a>.en_US
dc.identifier.digitalRICE1967en_US
dc.identifier.urihttps://hdl.handle.net/1911/104335en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.titleEstimation of repetition rate from signal and texture featuresen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentElectrical Engineeringen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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