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Technical Program

Paper Detail

Paper:	SPTM-L9.4
Session:	Affine Projection Algorithms
Time:	Friday, May 19, 17:30 - 17:50
Presentation:	Lecture
Topic:	Signal Processing Theory and Methods: Adaptive Systems and Filtering
Title:	Affine Projection Algorithms with Adaptive Regularization Matrix
Authors:	Young-Seok Choi, Pohang University of Science and Technology, Republic of Korea; Hyun-Chool Shin, Johns Hopkins School of Medicine, United States; Woo-Jin Song, Pohang University of Science and Technology, Republic of Korea
Abstract:	We propose a family of novel affine projection algorithms (APA) with adaptive regularization matrix. Conventional regularized APA (R-APA) uses a fixed and weighted identity matrix for regularization. The proposed algorithms incorporate a non-identity regularization matrix which is also dynamically updated. The matrix adaptation is based on the normalized stochastic-gradient of mean-square error. As a result, the efficient and robust algorithms are derived. Throughout experiments, we illustrate that the proposed algorithms show better performance than the conventional R-APA and comparable to the RLS algorithm in terms of the convergence rate and the misadjustment error.