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  Subspace identification through blind source separation

Grosse-Wentrup, M., & Buss, M. (2006). Subspace identification through blind source separation. IEEE Signal Processing Letters, 13(2), 100-103. doi:10.1109/LSP.2005.861581.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D2EB-A Version Permalink: http://hdl.handle.net/21.11116/0000-0004-9648-2
Genre: Journal Article

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Grosse-Wentrup, M1, Author              
Buss, M, Author
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 Abstract: Given a linear and instantaneous mixture model, we prove that for blind source separation (BSS) algorithms based on mutual information, only sources with non-Gaussian distribution are consistently reconstructed independent of initial conditions. This allows the identification of non-Gaussian sources and consequently the identification of signal and noise subspaces through BSS. The results are illustrated with a simple example, and the implications for a variety of signal processing applications, such as denoising and model identification, are discussed.

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 Dates: 2006-02
 Publication Status: Published in print
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 Identifiers: DOI: 10.1109/LSP.2005.861581
BibTex Citekey: 4979
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Title: IEEE Signal Processing Letters
Source Genre: Journal
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Pages: - Volume / Issue: 13 (2) Sequence Number: - Start / End Page: 100 - 103 Identifier: -