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A method is presented for designing optimal adaptive digital filters. The derivation is based upon filtering a desired signal which has been corrupted by a "noise" like signal so the least-square error between the filtered output and the desired output is minimized. The filter is contrasted with both the Levinson and Widrow filters. The greatest utility of the derived filters are in digital signal processing applications where real-time or stability are critical constraints.