Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
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| URI | http://purl.tuc.gr/dl/dias/FE586237-689D-4D4F-8B19-516C33D5A023 | - |
| Αναγνωριστικό | http://www.researchgate.net/profile/Vangelis_Sakkalis/publication/224163305_Comparative_analysis_of_time-frequency_methods_estimating_the_time-varying_microstructure_of_sleep_EEG_spindles/links/0fcfd50c74d6cb7439000000.pdf | - |
| Γλώσσα | en | - |
| Μέγεθος | 5 pages | en |
| Τίτλος | Comparative analysis of time-frequency methods estimating the time-varying microstructure of sleep EEG spindles | en |
| Δημιουργός | Zervakis Michalis | en |
| Δημιουργός | Ζερβακης Μιχαλης | el |
| Δημιουργός | Paparrigopoulos, T | en |
| Δημιουργός | H. Tsekou | en |
| Δημιουργός | Sakkalis, Vangelis | en |
| Δημιουργός | Golemati, S | en |
| Περίληψη | Parameter estimation for an assumed sleep EEG spindle model (AM-FM signal) is performed by using four time-frequency analysis methods. Results from simulated as well as from real data are presented. In simulated data, the Hilbert Transform-based method has the lowest average percentage error but produces considerable signal distortion. The Complex Demodulation and the Matching Pursuit-based methods have error rates below 10%, but the Matching Pursuit-based method produces considerable signal distortion as well. The Wavelet Transform-based method has the poorest performance. In real data, all methods produce reasonable parameter values. However, the Hilbert Transform and the Matching Pursuit- based methods may not be applicable for sleep spindles shorter than about 0.8 sec. Matching Pursuit-based curve fitting is utilized as part of the parameter estimation process. | en |
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Τύπος | Conference Full Paper | en |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2015-10-23 | - |
| Ημερομηνία Δημοσίευσης | 2006 | - |
| Θεματική Κατηγορία | Biomedicine | en |
| Βιβλιογραφική Αναφορά | en |
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