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A low-complexity strategy for speeding up the convergence of convex combinations of adaptive filters

In this work a low-complexity strategy for accelerating the convergence of convex combinations of adaptive filters is proposed. The idea is based on an instantaneous transfer of coefficients from a fast adaptive filter to a slow adaptive filter, which is performed according to a pre-defined window length. A theoretical model that is capable of predicting the excess mean squared error (EMSE) of the proposed strategy is also presented. Simulation results illustrate the good performance of the proposed strategy and the effectiveness of the proposed model to predict the EMSE.