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Blind source separation of nonstationary convolutively mixed signals in the subband domain

机译:子带域中非平稳卷积混合信号的盲源分离

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摘要

The paper proposes a new technique for blind source separation (BSS) in the subband domain using an extended lapped transform (ELT) decomposition for nonstationary, convolutively mixed signals. As identified by S. Araki et al. (see Proc. 4th Int. Symp. on Independent Component Analysis and Blind Signal Separation - ICA2003, p.499-504, 2003), the motivation for subband-based BSS is the drawback of frequency domain BSS when dealing with separating mixed speech signals over a few seconds resulting in few samples in individual frequency bins leading to poor separation performance. In the proposed approach, mixed signals are decomposed into subband components by an ELT and within each subband a time domain Newton BSS algorithm is employed based on the nonstationarity property of the input signals and the joint diagonalization of output correlation matrices with time varying second order statistics (SOS). This subband version is compared to a fullband version using the same BSS algorithm.
机译:这篇论文提出了一种新技术,用于子带域中的盲源分离(BSS),它使用扩展的重叠变换(ELT)分解来处理非平稳,卷积混合信号。如S. Araki等人所确定。 (参见独立分量分析和盲信号分离的第4篇国际征兆-ICA2003,第499-504页,2003年),基于子带的BSS的动机是在处理分离混合语音信号时频域BSS的缺点几秒钟后,单个频点中的采样数将减少,从而导致分离性能下降。在所提出的方法中,混合信号通过ELT分解为子带分量,并且在每个子带内,基于输入信号的非平稳性和输出相关矩阵的联合对角化以及时变二阶统计量,采用时域牛顿BSS算法(SOS)。使用相同的BSS算法将该子带版本与全带版本进行比较。

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