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Fractal dimension and classification of music

Identifieur interne : 000A32 ( Main/Exploration ); précédent : 000A31; suivant : 000A33

Fractal dimension and classification of music

Auteurs : M. Bigerelle [France] ; A. Iost [France]

Source :

RBID : ISTEX:2CA9497F83750DE966519D5FC559CF8F9C72DEC0

English descriptors

Abstract

Abstract: The fractal aspect of different kinds of music was analyzed in keeping with the time domain. The fractal dimension of a great number of different musics (180 scores) is calculated by the Variation method. By using an analysis of variance, it is shown that fractal dimension helps discriminate different categories of music. Then, we used an original statistical technique based on the Bootstrap assumption to find a time window in which fractal dimension reaches a high power of music discrimination. The best discrimination is obtained between 1/44100 and 16/44100 Hertz. We admit that to distinguish some different aspects of music well, the high information quantity is obtained in the high frequency domain. By calculating fractal dimension with the ANAM method, it was statistically proven that fractal dimension could distinguish different kinds of music very well: musics could be classified by their fractal dimensions.

Url:
DOI: 10.1016/S0960-0779(99)00137-X


Affiliations:


Links toward previous steps (curation, corpus...)


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