Two-dimensional joint process adaptive filtering via principal component support region

摘要

This paper describes a 2-D joint process adaptive filtering algorithm using the orthogonal property of the principal component support region in order to speed up the convergence rate. We also introduce the symmetrical sparse support region (SSSR) to reduce the computational burden of the duplicated support region (DSR). Computer simulation results are given to verify the performance of the proposed model.