摘要: The necessity of filtering noisy data generated by multidimensional processes arises in many diverse settings. direct application the Kalman-Bucy results is hindered dimensionality difficulties inherent problems. This paper shows that for linear steady-state problems significant reductions can be accomplished, thus making routine solution interesting