一种新的基于阶递归UD分解的块自适应算法

T. Furukawa, S. Yoshimoto, H. Kubota
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引用次数: 0

摘要

特别是自适应算法在自适应信号处理中起着重要的作用,迄今为止,各种技术已经做了大量的工作。其中,利用正交投影的算法最为人所知,其收敛特性可以用Moore-Penrose型广义逆矩阵表示。本文提出了一种新的块自适应算法,该算法利用阶更新UD分解可以有效地计算Moore-Penrose型广义矩阵。与传统的最后块自适应算法相比,该算法在过程中包含的除法更少,具有稳定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new block adaptive algorithm using order recursive UD factorization method
Adaptive algorithm especially plays the important role in adaptive signal processing, and much work has been proposed with various techniques until up to now. Among them, the algorithms using orthogonal projection are well known, which can be expressed with Moore-Penrose type generalized inverse matrix, with respect to the convergence characteristics. This paper presents a new block adaptive algorithm in which Moore-Penrose type generalized matrix can be efficiently calculated with order-update UD factorization. The proposed algorithm is expected to have stable property, since it includes less divisions in the procedures compared with the traditional last block adaptive algorithms.<>
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