Theoretical and Experimental Investigation of an Efficient SVD-based Near-lossless Compression Algorithm for Multichannel EEG Signals

In this paper, we investigate performance of a re-cently proposed near-lossless compression algorithm specifically devised for multichannel electroencephalograph (EEG) signals. The algorithm exploits the fact that singular value decomposition (SVD) is usually performed on EEG signals for denoising a...

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Vydané v:	2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA) s. 1 - 6
Hlavní autori:	Campobello, Giuseppe, Quercia, Angelica, Gugliandolo, Giovanni, Segreto, Antonino, Tatti, Elisa, Ghilardi, Maria Felice, Crupi, Giovanni, Quartarone, Angelo, Donato, Nicola
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 22.06.2022
Predmet:	biomedical signal processing Distortion electroencephalo-graph (EEG) Electroencephalography Memory management Near-lossless compression Noise reduction Signal processing algorithms singular value eecomposition (SVD) Task analysis Upper bound
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