Blind Separation of Noncircular Sources Via Approximate Joint Diagonalization of Augmented Charrelation Matrices

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• 作者：Xiaoming Gou (1)
  Zhiwen Liu (1)
  Jingyan Ma (1)
  Yougen Xu (1)
  
  1. School of Information and Electronics ; Beijing Institute of Technology ; Beijing ; 100081 ; China
  
• 关键词：Blind source separation ; Characteristic function ; Hessian matrix ; Joint diagonalization ; Noncircularity
• 刊名：Circuits, Systems, and Signal Processing
• 出版年：2015
• 出版时间：February 2015
• 年：2015
• 卷：34
• 期：2
• 页码：695-705
• 全文大小：361 KB
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• 刊物类别：Engineering
• 刊物主题：Electronic and Computer Engineering
  
• 出版者：Birkh盲user Boston
• ISSN：1531-5878

文摘

An augmented charrelation matrix (ACM), which can utilize both the conventional and the conjugate statistical information in the complex domain, is proposed. The ACM additionally makes use of the conjugate Hessian matrix (namely conjugate charrelation matrix) of the observations of noncircular sources. A blind separation scheme built on the approximate joint diagonalization (AJD) principle is introduced, which precedes some numerical examples to demonstrate the improved performance of the ACM-AJD approach compared with some algorithms in the literature.