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
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