Nonlinear acoustic echo cancellation using adaptive filters

The presence of nonlinearities irn acoustic paths affects the performance of the acoustic channels by generating nonlinear echoes. These nonlinear echoes are cancelled by introducing a new class of nonlinear adaptive filters, derived by the adaptive combination of filters. Such filters are derived from the functional link adaptive filter (FLAF) model defined by a nonlinear input expansion and a subsequent adaptive filtering. In order to provide robustness against the various degrees of nonlinearity and to solve the convergence drawbacks a modified architecture is derived from the conventional FLAF, known as collaborative functional link adaptive filter (CFLAF). Such architecture allows achieving the best performance regardless of the nonlinearity degree in the acoustic path. In this work adaptive algorithm based on stochastic gradient rule and RLS is used.