Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Variable Step-Size Proportionate Affine Projection Algorithm for Identification of Sparse Impulse Response | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2009 Article ID 150914 10 pages doi 2009 150914 Research Article A Variable Step-Size Proportionate Affine Projection Algorithm for Identification of Sparse Impulse Response Ligang Liu 1 2 Masahiro Fukumoto 1 Sachio Saiki 1 and Shiyong Zhang2 1 Department of Information Systems Engineering Kochi University of Technology 185 Miyanokuchi Kochi 782-8502 Japan 2 School of Computer Science Fudan University 220 Handan Road Shanghai 200433 China Correspondence should be addressed to Masahiro Fukumoto Received 13 January 2009 Revised 19 May 2009 Accepted 5 August 2009 Recommended by Jose Carlos Bermudez Proportionate adaptive algorithms have been proposed recently to accelerate convergence for the identification of sparse impulse response. When the excitation signal is colored especially the speech the convergence performance of proportionate NLMS algorithms demonstrate slow convergence speed. The proportionate affine projection algorithm PAPA is expected to solve this problem by using more information in the input signals. However its steady-state performance is limited by the constant step-size parameter. In this article we propose a variable step-size PAPA by canceling the a posteriori estimation error. This can result in high convergence speed using a large step size when the identification error is large and can then considerably decrease the steady-state misalignment using a small step size after the adaptive filter has converged. Simulation results show that the proposed approach can greatly improve the steady-state misalignment without sacrificing the fast convergence of PAPA. Copyright 2009 Ligang Liu et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. Introduction .
