A new class of sequential and adaptive algorithms with application to noise cancellation

A class of sequential and adaptive algorithms for parameter estimation are presented that are based on the iterative estimate-maximize (EM) algorithm. In some cases sequential algorithms are derived that perform an exact EM step in each recursion; an example for these cases is given for the linear least-squares problem. In general, however, it is necessary to approximate the EM iteration in order to develop sequential algorithms. The application of this class of algorithms to the two-microphone noise cancellation problem is described