Title :
The EEG Signal Process Based on EEMD
Author :
Xiao-jun, Zhu ; Shi-qin, Lv ; Fan Liu-juan ; Yu Xue-li
Author_Institution :
Coll. of Comput. Sci., Taiyuan Univ. of Technol., Taiyuan, China
Abstract :
Hilbert Huang Transform (HHT), which is based on EMD (Empirical Mode Decomposition) and Hilbert transform method, is a new signal analysis method. It suits for analyzing the non-linear and non-stationary signals, such as EEG signal particularly. The traditional EMD method has the Mode Mixing problem. Therefore a new method basing on Ensemble Empirical Mode Decomposition (EEMD) for processing the signal has been approached in this paper. This method can effectively ensure the integrity of signal´s mapping in the different regions through adding random white noise component into the original data, and overcome the mode mixing problem of traditional EMD decomposition.
Keywords :
Hilbert transforms; electroencephalography; medical signal processing; EEG signal process; EEMD; HHT; Hilbert Huang transform; bioelectric current; ensemble empirical mode decomposition; mode mixing problem; Brain modeling; Educational institutions; Electroencephalography; Time frequency analysis; Transforms; White noise; EEG; EEMD; EMD; Hilbert-Huang Transform; Mode Mixing; simulation;
Conference_Titel :
Intelligence Information Processing and Trusted Computing (IPTC), 2011 2nd International Symposium on
Conference_Location :
Hubei
Print_ISBN :
978-1-4577-1130-5
DOI :
10.1109/IPTC.2011.67