A state space approach for the modeling of nonstationary time series 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。
Numerical test results show that SVR has good ability of modeling nonstationary financial time series and good generalization under small data set available.
数值实验表明，SVR方法对非平稳的金融时间序列具有良好的建模和泛化能力。
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