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An EMD based time-frequency distribution and its application in EEG analysis / 生物医学工程学杂志
Journal of Biomedical Engineering ; (6): 990-995, 2007.
Article in Chinese | WPRIM | ID: wpr-346025
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.
Subject(s)
Full text: Available Index: WPRIM (Western Pacific) Main subject: Algorithms / Signal Processing, Computer-Assisted / Nonlinear Dynamics / Electroencephalography / Epilepsy / Methods Limits: Humans Language: Chinese Journal: Journal of Biomedical Engineering Year: 2007 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Algorithms / Signal Processing, Computer-Assisted / Nonlinear Dynamics / Electroencephalography / Epilepsy / Methods Limits: Humans Language: Chinese Journal: Journal of Biomedical Engineering Year: 2007 Type: Article