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Denoising using local projective subspace methods

Gruber, Peter, Stadlthanner, Kurt, Böhm, M., Theis, Fabian J., Tomé, A. M., Teixeira, A. R., Puntonet, Carlos G., Gorriz, J. M. and Lang, Elmar (2007) Denoising using local projective subspace methods. Neurocomputing 69 (13-15), pp. 1485-1501.

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In this paper we present previous termdenoisingnext term algorithms for enhancing noisy signals based on previous termLocalnext term 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 components resembling the signals can be detected by various ...


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Item type:Article
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
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Keywords:Local ICA; Delayed AMUSE; Projective subspace denoising embedding
Dewey Decimal Classification:500 Science > 570 Life sciences
Created at the University of Regensburg:Unknown
Item ID:16913
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