基于多网格线性方程解算器的自适应滤波

J. H. Husøy
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引用次数: 2

摘要

一种新的自适应滤波算法的发展方法是基于平稳迭代线性方程求解器的理论:一个经典的理查德森迭代,可能是先决条件,应用于Wiener-Hopf方程。在一个统一的框架内,用各种统计量的估计值代替了大量的经典和现代自适应滤波器。本文进一步从数值线性代数领域汲取灵感,利用多网格范式设计了一种简单、鲁棒且性能优于NLMS算法的自适应滤波器,该范式主要用于偏微分方程及其离散线性方程组的数值求解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An adaptive filter based on multigrid linear equation solvers
A recent and novel approach to the development of adaptive filtering algorithms is based on the theory of stationary iterative linear equation solvers: A classical Richardson iteration, possibly preconditioned, is applied to the Wiener-Hopf equation. Substituting estimates for various statistical quantities in the resulting recursion, a large number of classical and modern adaptive filters are developed with ease within a unified framework. Taking further inspiration from the field of numerical linear algebra, in this paper we make use of the multigrid paradigm, mostly used in the numerical solution of partial differential equations and their corresponding discretized linear equation sets, to devise a simple, yet robust adaptive filter with better performance than the NLMS algorithm.
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