Naslov
TFD Thresholding In Estimating The Number of EEG Components And The Dominant IF Using The Short-Term Rényi Entropy

Autori
Lerga, Jonatan ; Saulig, Nicoletta ; Lerga, Rebeka ; Štajduhar, Ivan

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
10th International Symposium on Image and Signal Processing and Analysis - ISPA 2017 / Kovačič, Stanislav ; Lončarić, Sven ; Kristan, Matej ; Štruc, Vitomir ; Vučić, Mladen - Ljubljana : University of Zagreb, Croatia, 2017, 80-85

ISBN
978-1-5090-4011-7

Skup
10th International Symposium on Image and Signal Processing and Analysis - ISPA 2017

Mjesto i datum
Ljubljana, Slovenija, 18.09.2017. - 20.09.2017

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Short-Term Rényi Entropy ; Instantaneous Frequency (IF) Estimation ; Time-Frequency Signal Analysis

Sažetak
Time-frequency (TF) based EEG signal analysis using the local or short-term R´enyi entropy often requires lowenergy cross-terms and noise suppression prior to the estimation of the local number of components and the dominant component instantaneous frequency (IF). This can be easily accomplished by thresholding in the TF domain with the preset TF threshold value, often chosen empirically. The paper investigates the sensitivity of the method based on the local R´enyi entropy to the chosen threshold value. The study was performed on real-life left and right hand movements EEG signals. As shown in the paper, the number of the EEG components extracted using the short- term R´enyi entropy is highly sensitive to the chosen TF threshold value, unlike the dominant IF which was shown to be highly robust to TF thresholding. Hence, characterization of the EEG signals using the short-term R´enyi entropy should include both detecting the number of EEG components and the dominant component IF estimation.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo

POVEZANOST RADA