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...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	2022 IEEE International Symposium on Medical Measurements and Applications (MeMeA) S. 1 - 6
Hauptverfasser:	Campobello, Giuseppe, Quercia, Angelica, Gugliandolo, Giovanni, Segreto, Antonino, Tatti, Elisa, Ghilardi, Maria Felice, Crupi, Giovanni, Quartarone, Angelo, Donato, Nicola
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 22.06.2022
Schlagworte:	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
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!