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dc.rights.licenseAll rights reserveden_US
dc.contributor.advisorVicente, Luis M.
dc.contributor.authorOvalles Torres, José R.
dc.date.accessioned2020-09-28T11:41:43Z
dc.date.available2020-09-28T11:41:43Z
dc.date.issued2014
dc.identifier.citationOvalles Torres, J. R. (2014). A wavelet-based approach for pitch classifiers [Unpublished manuscript]. Graduate School, Polytechnic University of Puerto Rico.en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12475/787
dc.descriptionDesign Project Article for the Graduate Programs at Polytechnic University of Puerto Ricoen_US
dc.description.abstractA pitch is a human classification method which allows ordering sounds in discrete harmonics frequencies. Although many of the practical pitch detection methods uses the autocorrelation and cepstrum techniques to detect audio pitch, a wavelet-based classifier was developed using wavelets to create a unique signal coding for each pure pitch signals. A comparative study of how the wavelets coefficients vary on each of the seven proposed pure pitch signals were given in this article. Also mathematical and illustrated examples of this study were presented as well. Key Terms - Autocorrelation, Classifier, KNN, Wavelets, Wavelets Transforms.en_US
dc.language.isoen_USen_US
dc.publisherPolytechnic University of Puerto Ricoen_US
dc.relation.ispartofElectrical Engineering;
dc.relation.ispartofseriesSpring-2014;
dc.relation.haspartSan Juanen_US
dc.subject.lcshHarmonic analysis
dc.subject.lcshSignal processing
dc.subject.lcshPolytechnic University of Puerto Rico--Graduate students--Research
dc.titleA Wavelet-Based Approach for Pitch Classifiersen_US
dc.typeArticleen_US
dc.rights.holderPolytechnic University of Puerto Rico, Graduate Schoolen_US


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