Referenced Items are not available for this document.
Complex maximization of nonGaussianity (CMN) has been shown to provide reliable separation of both circular and non-circular sources using a class of complex functions in the non-linearity. In this paper, we derive a fixed-point algorithm for blind separation of noncircular sources using CMN. We also introduce the adaptive CMN (A-CMN) algorithm that provides significant performance improvement by adapting the nonlinearity to the source distribution. The ability of A-CMN to adapt to a wide range of source statistics is demonstrated by simulation results.
Published in:
Machine Learning for Signal Processing, 2006. Proceedings of the 2006 16th IEEE Signal Processing Society Workshop on
Date of Conference: 6-8 Sept. 2006
- Page(s):
- 79 - 84
- ISSN :
- 1551-2541
- E-ISBN :
- 1-4244-0657-9
- Print ISBN:
- 1-4244-0656-0
- INSPEC Accession Number:
- 10185034
- Conference Location :
- Arlington, VA
- Digital Object Identifier :
- 10.1109/MLSP.2006.275526
- Product Type:
- Conference Publications
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