An improved affine projection tanh algorithm for robust adaptive filtering

Recently, an affine projection tanh (APT) algorithm has been designed based on optimization criteria with hyperbolic tangent function constraints. However, there is a significant steady-state error in the APT algorithm. To address this drawback, this article presents an improved APT (IAPT) algorithm based on the optimization framework with hyperbolic tangent function square constraints. It is shown that the proposed IAPT algorithm displays strong robustness, higher convergence speed, and smaller estimation error compared to affine projection (AP) algorithm, AP sign algorithm (APSA) and APT algorithms under the impulsive noise disturbance in the system identification application scenario.