Title :
Lossless EEG signal compression
Author :
Arnavut, Ziya ; Koak, H.
Author_Institution :
Dept. of Comput. Sci., SUNY Fredonia, Fredonia, NY, USA
Abstract :
In this work, we investigate the lossless compression of EEG signals using Burrows-Wheeler Transformation and linear prediction. We show that when compressing EEG signals utilization of linear prediction and Burrows-Wheeler Transformation yield better compression than the well-known techniques.
Keywords :
electroencephalography; medical signal processing; Burrows-Wheeler transformation; linear prediction; lossless EEG signal compression; Brain modeling; Compressors; Computer science; Context modeling; Electrocardiography; Electroencephalography; Epilepsy; Patient monitoring; Predictive models; Testing;
Conference_Titel :
Soft Computing, Computing with Words and Perceptions in System Analysis, Decision and Control, 2009. ICSCCW 2009. Fifth International Conference on
Conference_Location :
Famagusta
Print_ISBN :
978-1-4244-3429-9
Electronic_ISBN :
978-1-4244-3428-2
DOI :
10.1109/ICSCCW.2009.5379436
