Improved NSAF Algorithms with Variable Control Parameter Against Impulsive Noises

Abstract

Some improved normalized subband adaptive filter algorithms derived from nonlinear cost functions, such as the logarithmic function and the arctangent function, have shown splendid robustness against the impulsive noises. However, due to the usage of the constant control parameter in their cost functions, these algorithms need to make a balance between the steady-state error and the convergence rate, especially when the unknown impulse response changes suddenly. For settling this trade-off issue, a way of obtaining the variable control parameter (VCP) recursively is constructed by an exponential function in this paper. In the contexts of system identification and acoustic echo cancellation, simulation results testified the improved performance of these proposed VCP algorithms in terms of the convergence rate, steady-state error, and tracking capability.