Denoising based on wavelet and PCA signal compression

Abstract

The paper includes a presentation and comparison of principal component analysis (PCA) and wavelet transform approach to the reduction of noise contaminating the data. The elimination of the noise is achieved through compression and then decompression of the noisy data with some losses. In the paper the results of some numerical experiments are included and the choice of compression parameters discussed.

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Cite this paper

@article{Majkowski2005DenoisingBO, title={Denoising based on wavelet and PCA signal compression}, author={Andrzej Majkowski and R . Rak and M. Godziemba-Maliszewski}, journal={IEEE International Workshop on Intelligent Signal Processing, 2005.}, year={2005}, pages={70-73} }