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Abstract

An input signal X(j) is fed directly to the positive port of a summing function and is simultaneously fed through a parallel channel in which it is delayed, and passed through an adaptive linear transversal filter, the output being then subtracted from the instantaneous input signal X(j). The difference, X(j)-Y(j), between these two signals is the error signal .epsilon.(j). .epsilon.(j) is multiplied by a gain .mu. and fed back to the adaptive filter to readjust the weights of the filter. The weights of the filter are readjusted until .epsilon.(j) is minimized according to the recursive algorithm: ##EQU1## where the arrow above a term indicates that the term is a signal vector. Thus, when the means square error is minimized, W.sub.(j+1) =W.sub.(j), and the filter is stabilized.

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