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Proceedings Paper

Asymmetry and self-similarity in the wavelet spectrum
Author(s): Camilo Rodrigues Neto; Reinaldo Roberto Rosa; Fernando M. Ramos; Ademilson Zanandrea
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Paper Abstract

One of the most remarkable properties of wavelet transform is its ability to separate data into different scale contents. For data that show self-similar characteristics in every scale, like fractal landscape, the wavelet spectrum also shows self-similarity. Nevertheless, the situation is not so clear for time dependent data, like seismic geology, solar flares, among others systems that are known to contain self-organized criticality. It is not obvious that these properties will be present in the wavelet spectrum in the form of self-similarity. In this work, we apply two gradient field computational operators R2 yields R, the Complex Entropic Form and the Asymmetric Amplitude Fragmentation, as a mean to differentiate self-similarity from different sources.

Paper Details

Date Published: 26 October 1999
PDF: 9 pages
Proc. SPIE 3813, Wavelet Applications in Signal and Image Processing VII, (26 October 1999); doi: 10.1117/12.366849
Show Author Affiliations
Camilo Rodrigues Neto, National Institute for Space Research (Brazil)
Reinaldo Roberto Rosa, National Institute for Space Research (Brazil)
Fernando M. Ramos, National Institute for Space Research (Brazil)
Ademilson Zanandrea, National Institute for Space Research (Brazil)


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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