子空间估计和跟踪使用增强版的Oja算法

2001 IEEE Third Workshop on Signal Processing Advances in Wireless Communications (SPAWC'01). Workshop Proceedings (Cat. No.01EX471) Pub Date : 2001-03-20 DOI:10.1109/SPAWC.2001.923886

S. Attallah, K. Abed-Meraim

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引用次数: 4

摘要

我们提出了Oja(1992)算法的两个标准化版本(NOja和NOOja)，它们可用于估计向量序列的次要(噪声)和主要(信号)子空间。与Oja相比，新算法提供了更快的收敛性，更好的正交性和数值稳定性，但计算复杂性略有增加。这些算法可以找到许多应用，特别是在无线通信中。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Subspace estimation and tracking using enhanced versions of Oja's algorithm

We present two normalized versions of the Oja (1992) algorithm (NOja and NOOja) which can be used for the estimation of minor (noise) and principal (signal) subspaces of a vector sequence. The new algorithms offer, as compared to Oja, a faster convergence, a better orthogonality and numerical stability with a slight increase in computational complexity. These algorithms can find many applications, in particular, in wireless communications.

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2001 IEEE Third Workshop on Signal Processing Advances in Wireless Communications (SPAWC'01). Workshop Proceedings (Cat. No.01EX471)

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