Nonstationary signal analysis based on EMD and extremum points

Empirical mode decomposition (EMD) is a data driven processing algorithm, which has no predetermined filter. It is able to perfectly analyze the nonlinear and nonstationary signals. In EMD decomposition processing, the envelopes are computed by spline interpolation, which is time-consuming. In this work, firstly, we proposed a boundary extending method based on linear prediction and boundary extreme points adjusting, which reduce the end effects problem. And then, based on the straight line method, we proposed just using the extrema points to detect the extrema information about the signal, which is Extrema Points Empirical Mode Decomposition (EPEMD). By using the extrema points information, a fast and distinct frequency change detection method is proposed.