平稳随机时间序列的状态空间建模

Covariance-stationary stochastic time series state space modeling

在已知平稳随机时间序列样本数据的情况下，论述了如何采用正交投影算法和正交奇异值算法建立随机时间序列的状态空间模型和状态矢量估计。

According to the data of the covariance-stationary stochastic time series, we can get the state space modeling algorithm quickly and stably by singular value decomposition and orthogonal projection. This algorithm will be faster and more stable.