Abstract
The optimum filtering problem for a general class of linear distributed-parameter systems with colored observation noise is studied. The input stochastic disturbance is assumed to be white in time, but it may have correlation in space of any type. The optimum filter is derived through a learning theorem which gives the mean value and covariance matrix of a conditional distributed-paramete

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