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In this paper, the conditions for identifiability, separability and uniqueness of linear complex valued independent component analysis (ICA) models are established. These results extend the well-known conditions for solving real-valued ICA problems to complex-valued models. Relevant properties of complex random vectors are described in order to extend the Darmois-Skitovich theorem for complex-valued models. This theorem is used to construct a proof of a theorem for each of the above ICA model concepts. Both circular and noncircular complex random vectors are covered. Examples clarifying the above concepts are presented
Published in:
Information Theory, IEEE Transactions on
(Volume:52
,
Issue:
3
)
Date of Publication: March 2006
- Page(s):
- 1017 - 1029
- ISSN :
- 0018-9448
- INSPEC Accession Number:
- 8819750
- Digital Object Identifier :
- 10.1109/TIT.2005.864440
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 March 2006
- Issue Date :
- March 2006
- Sponsored by :
- IEEE Information Theory Society
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