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Eigenvalue problem approach to the blind source separation: Optimization with a reference signal

机译:盲源分离的特征值问题方法:参考信号优化

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The eigenvalue problem approach to the blind source separation [L. Molgedey and H. G. Schuster, Phys. Rev. Leb. 72, 3634 (1994)] is reinvestigated. The essential assumption is that the source signals should be statistically independent for the eigenvalue method to be applicable. When the source signals are correlated, unfortunately, this elegant approach faces a serious problem of optimization. We propose that by employing a reference signal in the separation procedure, the reconstructed signals that have an optimum minimum mismatch to the original sources can be obtained. The role and the criterion in choosing the reference signal will be extensively illustrated. Furthermore, the influences of nonzero correlation between different source signals, finite data length, and channel noises on signal separation will also be fully clarified. [S1063-651X(98)14110-7]. [References: 10]
机译:盲源分离的特征值问题方法[L. Molgedey和H.G.Schuster,物理学。牧师72,3634(1994)]进行了重新调查。基本假设是,源信号应在统计上独立于特征值方法适用。不幸的是,当源信号相关时,这种优雅的方法面临着严重的优化问题。我们建议通过在分离过程中使用参考信号,可以获得与原始信号源具有最佳最小失配的重构信号。将详细说明选择参考信号的作用和标准。此外,还将充分阐明不同源信号之间的非零相关性,有限的数据长度和通道噪声对信号分离的影响。 [S1063-651X(98)14110-7]。 [参考:10]

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