Blind Separation of Noisy Multivariate Data Using Second-Order Statistics: Remote-Sensing Applications
نویسندگان
چکیده
منابع مشابه
Blind Separation of Noisy Multivariate Data Using Second - Order Statistics
A second-order method for blind source separation of noisy instantaneous linear mixtures is presented and analyzed for the case where the signal order k and noise covariance GGH are unknown. Only a data set X of dimension n> k and of sample size m is observed, where X = AP + GW. The quality of separation depends on source-observation ratio }, the degree of spectral diversity, and the second-ord...
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This paper studies the blind source separation (BSS) problem with the assumption that the source signals are cyclostationary. Identifiability and separability criteria based on second-order cyclostationary statistics (SOCS) alone are derived. The identifiability condition is used to define an appropriate contrast function. An iterative algorithm (ATH2) is derived to minimize this contrast funct...
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ژورنال
عنوان ژورنال: IEEE Transactions on Geoscience and Remote Sensing
سال: 2009
ISSN: 0196-2892,1558-0644
DOI: 10.1109/tgrs.2009.2022325