A state space approach for the modeling of nonstationarytimeseries is presented.
非平稳时间序列的状态空间建模技术被用于陀螺漂移分析。
2
Nonlinear and nonstationarytimeseries are decomposed into a series of instrinsic mode functions and a residual trend item by the empirical mode decomposition (EMD).
非线性,非平稳的时间序列经过经验模分解,可以得到一组内模函数和一个基本的趋势项。
3
Because stock forecasting is a uncertain, nonlinear and nonstationarytimeseries problem, it is difficult to achieve a satisfying prediction effect by traditional methods.