{"title":"Study of the cepstral coefficient probability density function","authors":"J. Tourneret, B. Lacaze, F. Castanie","doi":"10.1109/SSAP.1992.246879","DOIUrl":null,"url":null,"abstract":"Cepstral coefficients, used in pattern recognition and classification with the k-nearest-neighbor method, give far better results than classification with the centroid distance rule. This paper proposes an analysis of cepstral coefficient probability density which reveals why the k-NN rule is in many instances a necessary tool in this particular representation space.<<ETX>>","PeriodicalId":309407,"journal":{"name":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSAP.1992.246879","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Cepstral coefficients, used in pattern recognition and classification with the k-nearest-neighbor method, give far better results than classification with the centroid distance rule. This paper proposes an analysis of cepstral coefficient probability density which reveals why the k-NN rule is in many instances a necessary tool in this particular representation space.<>
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