Signal separation in a symmetric adaptive noise canceler by output decorrelation

An algorithm for adaptive noise cancellation and signal separation is presented. It is an extension of the classical Widrow least-mean-square (LMS) noise canceler for the case of signal leakage into the noise reference. The algorithm is derived intuitively from the interpolation of the adaptive noise canceler as a decorrelator between signal estimate and noise in which the noise reference is replaced by a signal-free noise estimate. Thus, a symmetric adaptive decorrelator is obtained for signal separation, as the artificial distinction between signal and noise concepts has disappeared. The algorithm has its limitations as convergence to the desired solution and stability around it can only be guaranteed for a subclass of signal separation problems. These restrictions are rarely violated in real life problems, however, and seem to be fundamental to the signal separation problem rather than algorithm dependent