Selection of number of principal components for de-noising signals
- 20 June 2002
- journal article
- Published by Institution of Engineering and Technology (IET) in Electronics Letters
- Vol. 38 (13) , 664-666
- https://doi.org/10.1049/el:20020424
Abstract
Principal component analysis (PCA) is a transformation technique used to reduce the dimensionality of a dataset. Using delay embedding, it is possible to know a priori how many principal components to choose to obtain the optimum reconstruction. A novel nonlinear PCA-based scheme employing delay embedding is presented for the de-noising of communication signals.Keywords
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