A family of selective-tap algorithms for stereo acoustic echo cancellation

The use of adaptive filters employing tap-selection for stereophonic acoustic echo cancellation is investigated. We propose to employ subsampling of the tap-input vector, that is intrinsic to partial update schemes, to improve the conditioning of the tap-input autocorrelation matrix hence improving convergence. We investigate the effect of MMax tap-selection on the convergence rate for the single channel case by proposing a new measure which is then used as an optimization parameter in the development of our tap-selection scheme in the two channel case. The resultant exclusive maximum tap-selection is then applied to two channel NLMS, AP and RLS algorithms. Although our main motivation is not the reduction of complexity of SAEC, the proposed tap-selection nevertheless brings significant computation savings in additional to an improved rate of convergence over algorithms using only a nonlinear preprocessor.