时变系统的Laguerre模型辨识及设计变量（2） ——Kalman滤波法
Identification of Laguerre Model and Design Variable for Time-varying Systems(2) ------Kalman filter algorithms
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摘要: 文章考虑动态线性系统的时变参数是平稳的AR（1）变量，系统为时变的Laguerre模型时的传递函数估计的均方误差（MSE）。在缓慢时变和高阶模型下，利用Kalman滤波算法，得到MSE的近似表达式。最后得到了Kalman滤波算法的设计变量的最优解。
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关键词:
- 时变系统 /
- MSE /
- Laguerre模型 /
- 设计变量
Abstract: It is supposed that the time-varying parameters included in the system are stationary AR(1) variable. The estimate of the mean square error (MSE) of transfer function for time-varying Laguerre model is discussed. The approximate expression of MSE for Kalman filter algorithms can be derived under following assumptions:the dynamic of the system is slowly changing, the adaptation is also quite slow and the order of model system is high enough. Using Laguerre model instead of FIR model,the MSE will be reduced and the order of Laguerre model is reduced as well. The optimization problems for design variables of time-varying system identification algorithms are discussed. -
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