A Prediction Method for Time Series Based on Hilbert-Huang Transform and ARMA Model
MA Liang-lian · Journal of Jianghan University · 2014
A prediction method for time series based on Hilbert-Huang transform and ARMAmodel is proposed. The Hilbert-Huang transform is used to decompose the original time series into anumber of intrinsic mode function components and the instantaneous frequencies and amplitudes ofeach intrinsic mode function component are obtained. Then the ARMA model of each instantaneousfrequency and amplitude sequence is established. Finally,ARMA prediction model of the originalsequence is obtained through compounding. Experimental examples demonstrate that the methodbased on Hilbert-Huang transform and ARMA model can be applied to predict non-stationary timeseries effectively.