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A matrix-pencil approach to blind separation of non-white sources in white noise

机译:矩阵铅笔方法在白噪声中盲分离非白源

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The problem of blind source separation in additive white noise is an important problem in speech, array and acoustic signal processing. In general this problem requires the use of higher order statistics of the received signals. However for many signal sources, such as speech with distinct non-white power spectral densities, second order statistics of the received signal mixture can be exploited for signal separation. While previous approaches often assume that additive noise is absent or that the noise correlation matrix is known, we propose a simple and yet effective signal extraction method for signal source separation under unknown white noise. This new and unbiased signal extractor is derived from the matrix pencil formed between output auto-correlation matrices at different delays. Simulation examples are presented.
机译:加性白噪声中盲源分离的问题是语音,阵列和声信号处理中的重要问题。通常,此问题需要使用接收信号的高阶统计量。但是,对于许多信号源(例如具有不同的非白功率谱密度的语音),可以将接收到的信号混合的二阶统计信息用于信号分离。尽管先前的方法通常假定不存在加性噪声或已知噪声相关矩阵,但我们提出了一种简单而有效的信号提取方法,用于在未知白噪声下进行信号源分离。这种新的,无偏的信号提取器是由在不同延迟下的输出自相关矩阵之间形成的矩​​阵笔得出的。给出了仿真示例。

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