An EMD based time-frequency distribution and its application in EEG analysis.
- Author:
Xiaobing LI
1
;
Meng CHU
;
Tianshuang QIU
;
Haiping BAO
Author Information
1. Department of Electronic Engineering, Dalian University of Technology, Dalian 116024, China.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Electroencephalography;
methods;
Epilepsy;
physiopathology;
Humans;
Nonlinear Dynamics;
Signal Processing, Computer-Assisted
- From:
Journal of Biomedical Engineering
2007;24(5):990-995
- CountryChina
- Language:Chinese
-
Abstract:
Hilbert-Huang transform (HHT) is a new time-frequency analytic method to analyze the nonlinear and the non-stationary signals. The key step of this method is the empirical mode decomposition (EMD), with which any complicated signal can be decomposed into a finite and small number of intrinsic mode functions (IMF). In this paper, a new EMD based method for suppressing the cross-term of Wigner-Ville distribution (WVD) is developed and is applied to analyze the epileptic EEG signals. The simulation data and analysis results show that the new method suppresses the cross-term of the WVD effectively with an excellent resolution.
