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BLIND MISO DECONVOLUTION USING THE DISTRIBUTION OF OUTPUT DIFFERENCES

机译:使用产出差异的分布盲味噌卷积

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We present a novel blind identification and source separation method for linear Multi Input Single Output (MISO) convolutive systems driven by PAM sources. The method is based on the distribution estimation of the differences of pairs of outputs. We show that the most likely differences are the ones corresponding to the columns of the mixing matrix (upto a sign). The columns can be arranged in the correct order by using the Toeplitz property of the submatrices forming the overall transfer matrix. Thus the problem is transformed into the density estimation problem. The method is conceptually simple and can work with relatively small data sets although it is exponentially complex with the channel length or the number of input signals.
机译:我们提出了一种新的PAM源驱动的线性多输入单输出(MISO)卷曲系统的新颖盲识别和源分离方法。该方法基于对输出对差异的分布估计。我们表明,最可能的差异是对应于混合矩阵的列(UPTO标志)的差异。可以通过使用形成整体传递矩阵的子曲线的Toeplitz属性来按正确顺序排列列。因此,问题被转换为密度估计问题。该方法在概念上简单,并且可以使用相对较小的数据集,尽管它与信道长度或输入信号的数量是指数复杂的。

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