Fast Estimation of Optimal Sparseness of Music Signals

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Abstract

We want to use a variety of sparseness measured applied to ‘the minimal L1 norm representation' of a music signal in an overcomplete dictionary as features for automatic classification of music. Unfortunately, the process of computing the optimal L1 norm representation is rather slow, and we therefore investigate the use of matching pursuit, alternating projection, and Moore-Penrose inverse for estimating the result of applying two different sparseness measures to ‘the minimal L1 norm representation' without actually computing this representation.

Original languageEnglish
Title of host publicationProceedings of SPRRA 2006
Number of pages4
PublisherACTA Press
Publication date2006
ISBN (Print)0889865809
ISBN (Electronic)0889865825
Publication statusPublished - 2006
EventThe Third IASTED International Conference on Signal Processing, Pattern Recognition, and Applications - Innsbruck, Austria
Duration: 15 Feb 200617 Feb 2006

Conference

ConferenceThe Third IASTED International Conference on Signal Processing, Pattern Recognition, and Applications
Country/TerritoryAustria
CityInnsbruck
Period15/02/200617/02/2006

Keywords

  • Sparse representation
  • sparse decomposition
  • music

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