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  • 标题:Equivalence between Frequency-Domain Blind Source Separation and Frequency-Domain Adaptive Beamforming for Convolutive Mixtures
  • 本地全文:下载
  • 作者:Shoko Araki ; Shoji Makino ; Yoichi Hinamoto
  • 期刊名称:EURASIP Journal on Advances in Signal Processing
  • 印刷版ISSN:1687-6172
  • 电子版ISSN:1687-6180
  • 出版年度:2003
  • 卷号:2003
  • 期号:12
  • 页码:1157-1166
  • DOI:10.1155/S1110865703305074
  • 出版社:Hindawi Publishing Corporation
  • 摘要:

    Frequency-domain blind source separation (BSS) is shown to be equivalent to two sets of frequency-domain adaptive beamformers (ABFs) under certain conditions. The zero search of the off-diagonal components in the BSS update equation can be viewed as the minimization of the mean square error in the ABFs. The unmixing matrix of the BSS and the filter coefficients of the ABFs converge to the same solution if the two source signals are ideally independent. If they are dependent, this results in a bias for the correct unmixing filter coefficients. Therefore, the performance of the BSS is limited to that of the ABF if the ABF can use exact geometric information. This understanding gives an interpretation of BSS from a physical point of view.

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