Table of Contents
ISRN Signal Processing
Volume 2012 (2012), Article ID 457152, 10 pages
Research Article

Spectral Intrinsic Decomposition Method for Adaptive Signal Representation

1Laboratoire Images, Signaux et Systémes Intelligents (LISSI-E.A.3956), Université Paris Est Créteil Val de Marne, France
2Laboratoire d’Analyse, Numérique et d’Informatique (LANI), Universite Gaston Berger (UGB), Saint-Louis BP 234, Senegal
3Ecole Polytechnique de Thiès, Thiès BP A10, Senegal
4Département de Mathématique et Informatique, Faculté des Scinces et Technique, Université Cheikh Anta Diop de Dakar, Dakar BP 5005, Senegal

Received 12 October 2012; Accepted 31 October 2012

Academic Editors: C.-C. Hu and K. Wang

Copyright © 2012 Oumar Niang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We propose a new method called spectral intrinsic decomposition (SID) for the representation of nonlinear signals. This approach is based on the spectral decomposition of partial differential equation- (PDE-) based operators which interpolate the characteristic points of a signal. The SID’s components which are the eigenvectors of these PDE interpolation operators underlie the new signal decomposition-reconstruction method. The usefulness and the efficiency of this method is illustrated, in signal reconstruction or denoising aim, in some examples using artificial and pathological signals.