Abstract
The estimation of nonstationary stochastic process mean is suggested as the sum of two components, from which the first is the preliminery estimation and the next is chosen from conditions of mean-square error minimum. Unlike other known methods the estimation is got in evident form. The conditions, under which the estimation is optimal in the class of linear estimation have been determined. Nonlinear estimations are got recurrently. The modification of the linear estimation for the problem of mean filtration under coditions of a priori ambiguity is considered. The realized filter is constructed in recurrent form.
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