Variable Step Size Methods of the Hybrid Affine Projection Adaptive Filtering Algorithm under Symmetrical Non-Gaussian Noise

Abstract

The idea of variable step-size was introduced into the Hybrid Affine Projection Algorithm (H-APA) and we propose two variable step size algorithms based on H-APA, which are called the Variable Step-Size Hybrid Affine Projection Algorithm (VSS-H-APA) and the Modified Variable Step-Size Hybrid Affine Projection Algorithm (MVSS-H-APA). These are two variable-step algorithms aim to further improve the robust performance and convergence speed of H-APA under non-Gaussian noise. This allows for faster convergence while maintaining stability. The MVSS-H-APA goes further than VSS-H-APA to estimate the noise in order to achieve better convergence performance. The proposed algorithm performs better than the existing algorithms in system identification under symmetric non-Gaussian noise.

Variable-Step-Size Efficient Proportionate Affine Projection Sign Algorithms

“…Numerical simulation results confirm that our proposed algorithms have better filtering performance as compared to the existing SGCI-M-IPAPSA-type algorithms, with respect to the convergence rate with non-Gaussian impulsive interferences for sparse system identification, abrupt changes and colored inputs. Certainly, the core ideas of the proposed VSS ways not only enrich adaptive filter theory, but can also be applied to other algorithms and domains, such as echo cancellation application, machine learning and so on [1,12,18,[22][23][24][25][26][27][28][29][30].…”