Set-Membership Parial Update SMFTF Algorithm For Acoustic Echo Cancellation

Abstract

In recent years, computational complexity reduction (CCR) has gained greater importance in the development of dedicated adaptive algorithms in the field of acoustic echo cancellation (AEC). In this paper, a low-cost, adaptive filtering algorithm is proposed on the basis of the Reduced Partial Update Simplified Fast Transversal Filter (RPU- SMFTF) algorithm and Set Membership (SM) principle. The suggested algorithm is termed Set Membership-RPU-SMFT algorithm (SM-RPU-SMFTF). The benefits of the suggested algorithm, as opposed to the Normalized Least Mean Square (NLMS) and RPU-SMFTF adaptive algorithms, are outlined using simulation results. From the results, we infer that the SM-RPUSMFTF algorithm provides a good convergence phase, tracking ability and better steady-state phase than the other comparison algorithms with reduced the computational complexity.