LAUSR

The usage of low-quality components in communicating devices may introduce nonlinearity in the audio signals. The degree of nonlinearity may vary over time due to the nonstationary nature of audio signals. In the presence of nonlinear audio signals, the performance of an acoustic echo cancellation (AEC) scheme is impacted by two major limitations. The first one is related to the modeling accuracy, and the second one is related to the adaptation performance. The issue of modeling accuracy exists because the available nonlinear AEC (NAEC) schemes consider the nonlinearity as time-invariant and employ a fixed architecture to model the echo path. The adaptation performance issue occurs due to the conflicting requirements of fast convergence and low steady-state error. There is a need for an architecture that not only models the nonlinearity efficiently but also provides better performance in terms of convergence. In this paper, three new architectures convex combination functional link adaptive filter (CC-FLAF), improved CC-FLAF (ICC-FLAF), and variable step size CC-FLAF (VSSCC-FLAF) are proposed to overcome the above limitations. The proposed architectures are based on the combination of adaptive filters and variable step size approach. Computer simulations demonstrate the effectiveness of proposed architectures, in improving the nonlinear modeling performance for NAEC applications.