Pseudo-affine projection algorithm's for multichannel active noise control

作     者：Albu, Felix Bouchard, Martin Zakharov, Yuriy 

作者机构：Fotonat Romania SRL Bucharest Romania Univ Politehn Bucuresti Fac Elect Telecommun & Informat Technol Bucharest Romania Univ Ottawa Sch Informat Technol & Engn Ottawa ON K1N 6N5 Canada Univ York Dept Elect York YO10 5DD N Yorkshire England 

出 版 物：《IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING》 (IEEE Trans. Audio Speech Lang. Process.)

年 卷 期：2007年第15卷第3期

页      面：1044-1052页

核心收录：

主　　题：adaptive filtering dichotomous coordinate descent fast affine projection algorithms Gauss-Seidel solving scheme multichannel active noise control 

摘      要：For feedforward multichannel active noise control (ANC) systems, the use of adaptive finite-impulse response (FIR) filters is a popular solution, and the multichannel filtered-x least-mean-square (FX-LMS) algorithm is the most commonly used algorithm. The drawback of the FX-LMS is the slow convergence speed, especially for broadband multichannel systems. Recently, some fast affine projection algorithms have been introduced for multichannel ANC, as an interesting alternative to the FX-LMS algorithm. They can provide a significantly improved convergence speed at a reasonable additional computational cost. Yet, the additional computational cost or the potential numerical instability in some of the recently proposed algorithms can prevent the use of those algorithms for some applications. In this paper, we propose two pseudo-affine projection algorithms for multichannel ANC: one based on the Gauss-Seidel method and one based on dichotomous coordinate descent (DCD) iterations. It is shown that the proposed algorithms typically have a lower complexity than the previously published fast affine projection algorithms for ANC, with very similar good convergence properties and good numerical stability. Thus, the proposed algorithms are an interesting alternative to the standard FX-LMS algorithm for ANC, providing an improved performance for a computational load of the same order.