一种分离低维信号的ICA快速算法

汤影; 李建平; 吴淮

doi:10.3724/SP.J.1004.2011.00794

一种分离低维信号的ICA快速算法

doi: 10.3724/SP.J.1004.2011.00794

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- 被引次数: 0
出版历程
- 收稿日期: 2009-10-16
- 修回日期: 2011-02-22
- 刊出日期: 2011-07-20

A Simple and Accurate ICA Algorithm for Separating Mixtures of Up to Four Independent Components

摘要

摘要: 介绍了一种基于低维反对称矩阵指数的快速独立分量分析算法. 由于算法中牵涉到的矩阵指数具有解析闭合形式的表达, 因而算法中使用到的矩阵指数以及最优下降方向均可解析地得到. 另外, 我们纠正了在别的文献中建立的四维反对称矩阵指数表达式中的两个错误. 最后, 我们用仿真验证了算法. 实验结果表明: 相比于广为应用的Extended InfoMax和FastICA算法, 本文算法能得到更佳的分离性能.
- 独立分量分析 /
- 矩阵指数 /
- 闭形式
Abstract: This paper introduces an algorithm for independent component analysis (ICA) using explicit closed forms of two-, three- and four-dimensional antisymmetric matrix exponentials, based on which both the search direction and matrix exponentials can be directly computed in each iteration without any approximation. In addition, two errors have been corrected for the representation of four-dimensional antisymmetric matrix exponentials that were established in other works. Simulations show that the algorithm converges fast and can achieve better performance than the well-known Extended InfoMax and FastICA algorithms for mixtures of up to four independent components.
- Independent component analysis (ICA) /
- matrix exponential /
- closed form

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[1]

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