Simple algorithms for decorrelation-based blind source separation

S. Douglas
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引用次数: 3

Abstract

We present simple adaptive algorithms that perform blind source separation for spatially-independent and temporally-correlated source signals. The proposed algorithms are modified versions of a well-known natural gradient prewhitening scheme, and the simplest version has almost the same complexity as this prewhitening method. We provide a stationary point analysis of our schemes, proving that the only locally-stable stationary point results in separated sources with unit variances and a guaranteed output ordering. We also show how to modify the approaches so that joint subspace analysis and decorrelation-based source separation are performed. Simulations verify the separation capabilities of the schemes.
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基于去相关的盲源分离的简单算法
我们提出了简单的自适应算法,对空间独立和时间相关的源信号进行盲源分离。所提出的算法是一种著名的自然梯度预白化方案的改进版本,最简单的版本具有与该预白化方法几乎相同的复杂度。我们提供了我们的方案的平稳点分析,证明了唯一的局部稳定的平稳点导致具有单位方差的分离源和保证的输出顺序。我们还展示了如何修改这些方法,以便执行联合子空间分析和基于去相关的源分离。仿真验证了该方案的分离能力。
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