Title :
Mean-Square Deviation Analysis of Affine Projection Algorithm
Author :
Park, PooGyeon ; Lee, Chang Hee ; Ko, Jeong Wan
Author_Institution :
Div. of IT Convergence Eng., Pohang Univ. of Sci. & Technol., Pohang, South Korea
Abstract :
This paper presents an improved mean-square deviation (MSD) analysis of the standard affine projection algorithm (APA) based on two distinctive features. First, the propagation model of the error covariance includes the cross-correlation between the current weight error vector and the prior measurement noises associated with the reused inputs; such a cross-correlation has merely been considered previously. Second, the analysis based on n most recent accumulated iterations, rather than a typical analysis based on a current single iteration, is suggested to reveal a previously unseen phenomenon, where n denotes the tap-length of the filter. Simulation results are in better agreement with the proposed theoretical results, than the previous theoretical ones, over a wide range of parameters such as tap-length, projection order, and step-size.
Keywords :
adaptive filters; correlation methods; covariance analysis; least mean squares methods; afflne projection algorithm; cross-correlation; current weight error vector; error covariance; filter tap length; mean-square deviation analysis; most recent accumulated iterations; prior measurement noises; projection order; propagation model; reused inputs; step size; Adaptive filters; Covariance matrix; Mean square error methods; Noise measurement; Projection algorithms; Steady-state; Adaptive filters; affine projection algorithm (APA); mean-square deviation (MSD);
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2011.2165709