高技术通讯（英文版）2002，Vol.8Issue(2)：47-50,4.
The Study of a New Method for Forecasting Non-stationary Series
The Study of a New Method for Forecasting Non-stationary Series
摘要
Abstract
A new method for forecasting non-stationary series is developed. Its steps are as follows: Step 1. Data delaminating. Non-stationary series is delaminated into several multi-scale steady data layers and one trend layer. Step 2. Modeling and forecasting each stationary data layer. Step 3. Imitating trend layer using polynomial. Step 4. Combining the forecasting layers and imitating layer into one series. The EMD (Empirical Mode Decomposition) method suitable to process non-stationary series is selected to delaminate data, while ARMA (Auto Regressive Moving Average) model is employed to model and forecast stationary data layer and least square error method for trend layer regression. Aiming at forecasting length, forecasting orientation and selective method, experiments are performed for SAR (Synthetic Aperture Radar) images. Finally, an example is provided, in which the whole SAR image is restored via the method proposed by this paper.关键词
non-stationary series/forecasting/data delaminating/ARMA model/EMD/SAR imageKey words
non-stationary series/forecasting/data delaminating/ARMA model/EMD/SAR image分类
信息技术与安全科学引用本文复制引用
..The Study of a New Method for Forecasting Non-stationary Series[J].高技术通讯（英文版）,2002,8(2):47-50,4.基金项目
Supported by the High Technology Research and Development Program of China. （）
