Abstract
A new formulation of prediction of the values of a random process generated by white noise passing through a linear filter was discussed. It was assumed that observations were carried out in an unknown irregular constrained noise and the coefficients of signal transformation in the observation channel were unknown random variables. A randomized variant of the linear predicting filter which, under certain conditions, is superior to the minimax algorithms was proposed.
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Granichin, O.N. Nonminimax Filtering in Unknown Irregular Constrained Observation Noise. Automation and Remote Control 63, 1482–1488 (2002). https://doi.org/10.1023/A:1020090422744
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DOI: https://doi.org/10.1023/A:1020090422744