Title :
EEG time-frequency analysis based on the improved S-transform
Author :
Zhang Shaobai ; Huang Dandan
Author_Institution :
Comput. Dept., Nanjing Univ. of Posts & Telecommun., Nanjing, China
Abstract :
S-transform, which is a combination of short-time Fourier transform and wavelet transform, has attract intensive interest in recent years as an important tool to investigate non-stationary signal time-frequency distribution. S transform can be self-improved by the EEG characteristics to select a suitable mother wavelet. The improved S-transform will be used to analyze the time-frequency of the EEG characters. A comparison among the Short-time Fourier transform, wavelet transformation and the improved S-transform indicates that improved S-transform gives the best energy distribution in the time-frequency filed.
Keywords :
Fourier transforms; electroencephalography; signal processing; time-frequency analysis; wavelet transforms; EEG characteristics; EEG time-frequency analysis; improved S-transform; nonstationary signal time-frequency distribution; short-time Fourier transform; wavelet transform; Computers; Educational institutions; Electroencephalography; Electronic mail; Time-frequency analysis; Wavelet transforms; Electroencephalography(EEG); S transform; Time-frequency analysis; Wavelet Transform;
Conference_Titel :
Control and Decision Conference (CCDC), 2013 25th Chinese
Conference_Location :
Guiyang
Print_ISBN :
978-1-4673-5533-9
DOI :
10.1109/CCDC.2013.6561537