Generalized Correntropy Induced Metric Memory-Improved Proportionate Affine Projection Sign Algorithm and Its Combination

Abstract

In this brief, an efficient memory-improved proportionate affine projection sign algorithm with the generalized correntropy induced metric (GCI-M-IP-APSA) is proposed to modify the filtering performance for sparse system identification. In addition, a simplified implementation of GCI-M-IP-APSA is derived, and called as SGCI-M-IP-APSA, which has lower computational complexity and realizes comparable filtering performances with that of GCI-M-IP-APSA. However, the major limitation of proposed APSA-type algorithm is a poor convergence behavior in non-stationary situations. To overcome such issue, a convex combination method is applied to SGCI-M-IP-APSA to enhance the tracking performance. The good performances of proposed algorithms are verified in sparse system identifications with impulsive noise and abrupt changes.