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A procedure is given for optimizing the sequential estimation of a random variable in the mean-square sense, with the constraint that the data must be summarized by a finite-valued statistic. This finite-valued statistic can be considered to be the memory of the processor. The estimate is constrained to be a function of the contents of the memory and the time of the estimate. An example is given to illustrate the results.