【摘要】 Hilbert-Huang变换是一种新的分析非线性非平稳信号的时频方法,这种方法的关键部分是经验模态分解(EMD)方法,任何复杂的信号都可以通过EM D分解为有限数目并且具有一定物理意义的固有模态函数。我们结合该方法给出一种抑制Wigner-Ville分布交叉项的新方法,并将其应用于癫痫脑电信号(EEG)中,且得到了比较好的结果。更多还原

【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.更多还原