The Empirical Mode Decomposition Process of non-stationary signals
The Hilbert-Huang transform is a new method for analysing nonlinear and non-stationary data, and the empirical mode decomposition is key part of the method. The transform method raised by Norden E. Huang and others. The transform method is applied in many areas of signal analysis. In this paper, the precipitation data of Beijing is used as the studydata. The data is decomposed by empirical mode decomposition method. Then with Space-time index method, the author probes dynamical non-stationary in the original data and the decomposition data ,and made research to empirical mode decomposition process of the nonstationary signals . Finally the conclusion is that the precipitation time series is truly containing the non-stable factor,and with the decomposition, non-stationarity is weaker and weaker in the experience mode decomposition, the low frequency components non- stationary is very weak.
non-stationary Time Series EMD
Xuan Zhaoyan Xie Shiman Sun Qiuyan
College of Mechanical Engineering Hebei Polytechnic university Tangshan City, China
国际会议
长沙
英文
3120-3123
2010-03-13（万方平台首次上网日期，不代表论文的发表时间）