Denoising using local projective subspace methods

In this paper we present denoising algorithms for enhancing noisy signals based on Local ICA (LICA), Delayed AMUSE (dAMUSE) and Kernel PCA (KPCA). The algorithm LICA relies on applying ICA locally to clusters of signals embedded in a high-dimensional feature space of delayed coordinates. The compone...

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Bibliographic Details
Main Author: Gruber, P. (author)
Other Authors: Stadlthanner, K. (author), Böhm, M. (author), Theis, F. J. (author), Lang, E. W. (author), Tomé, A. M. (author), Teixeira, A. R. (author), Puntonet, C. G. (author), Gorriz Saéz, J. M. (author)
Format: article
Language:eng
Published: 1000
Subjects:
Local ICA
Delayed AMUSE
Projective subspace denoising embedding
Online Access:http://hdl.handle.net/10773/5806
Country:Portugal
Oai:oai:ria.ua.pt:10773/5806

Internet

http://hdl.handle.net/10773/5806

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