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On application of rational Discrete Short Time Fourier Transform in epileptic seizure classification

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
Otsikko2014 IEEE International Conference on Acoustics, Speech and Signal processing (ICASSP), May 4-9 2014, Florence, Italy
JulkaisupaikkaPiscataway
KustantajaIEEE
Sivut5839-5843
Sivumäärä5
ISBN (elektroninen)978-1-4799-2893-4
ISBN (painettu)978-1-4799-2892-7
DOI - pysyväislinkit
TilaJulkaistu - 2014
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING -
Kesto: 1 tammikuuta 19001 tammikuuta 2000

Julkaisusarja

NimiIEEE International Conference on Acoustics, Speech and Signal Processing
KustantajaIEEE
ISSN (painettu)1520-6149

Conference

ConferenceIEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING
Ajanjakso1/01/001/01/00

Tiivistelmä

This work deals with an adaptive and localized time-frequency representation of time-series signals based on rational functions. The proposed rational Discrete Short Time Fourier Transform (DSTFT) is used for extracting discriminative features in EEG data. We take the advantages of bagging ensemble learning and Alternating Decision Tree (ADTree) classifier to detect the seizure segments in presence of seizure-free segments. The effectiveness of different rational systems is compared with the classical Short Time Fourier Transform (STFT). The comparative study demonstrates that Malmquist-Takenaka rational system outperforms STFT while it can provide a tunable time-frequency representation of the EEG signals and less Mean Square Error (MSE) in the inverse transform. © 2014 IEEE.

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