双线性时间序列模型参数估计的最优滤波方法
AN OPTIMAL FILTERING ALGORITHM FOR PARAMETER ESTIMATION OF BILINEAR TIME SERIES MODEL
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摘要: 本文给出了一种用于双线性时间序列模型参数估计的自适应Kalman滤波器，在滤波过程中对误差协方差阵进行监控，使Kalman增益矩阵不趋于零，以保证观测数据对滤波的校正作用，并通过仿真例子将它和递推预报误差估计方法进行了比较．Abstract: A parameter estimation algorithm for bilinear time series model which is based on Kalman filtering is proposed in this paper. To overcome the divergence of the filter, the prediction error covariance matrix is monitered, and is reset when necessary. A simulation example is given to compare this algorithm with the recursive prediction error psrameter estimator.
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