Using the methods of time series spectral analysis and Kalman filter, this article discussed the additive problems of two stochastic processes, mainly Auto Regression Moving Average (ARMA) processes.
An ARMA innovation model and the state optimal filter are designed by modern time series analysis method.
结合现代时间序列分析方法，并根据新息模型设计了状态最优滤波器。
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Using the modern time series analysis method, this paper presents a new self - tuning deconvolution filter for unknown multivariable ARMA signal observed through a known linear system.