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Proceedings Paper

Nondyadic decomposition algorithm with Meyer's wavelet packets: an application to EEG signal
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Paper Abstract

In this paper, we propose an original decomposition scheme based on Meyer's wavelets. In opposition to a classical technique of wavelet packet analysis, the decomposition is an adaptative segmentation of the frequential axis which does not use a filters bank. This permits a higher flexibility in the band frequency definition. The decomposition computes all possible partitions from a sequential space: it does not only compute those that come from a dyadic decomposition. Our technique is applied on the electroencephalogram signal; here the purpose is to extract a best basis of frequential decomposition. This study is part of a multimodal functional cerebral imagery project.

Paper Details

Date Published: 26 October 1999
PDF: 12 pages
Proc. SPIE 3813, Wavelet Applications in Signal and Image Processing VII, (26 October 1999); doi: 10.1117/12.366834
Show Author Affiliations
Philippe Carre, IRCOM-SIC/Univ. de Poitiers (France)
Noel Richard, IRCOM-SIC/Univ. de Poitiers (France)
Christine Fernandez-Maloigne, IRCOM-SIC/Univ. de Poitiers (France)
Joel Paquereau, IRCOM-SIC/Univ. de Poitiers (France)


Published in SPIE Proceedings Vol. 3813:
Wavelet Applications in Signal and Image Processing VII
Michael A. Unser; Akram Aldroubi; Andrew F. Laine, Editor(s)

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