Blind Separation of Gaussian Sources With General Covariance Structures: Bounds and Optimal Estimation

We consider the separation of Gaussian sources exhibiting general, arbitrary (not necessarily stationary) covariance structures. First, assuming a semi-blind scenario, in which the sources' covariance structures are known, we derive the maximum likelihood estimate of the separation matrix, as w...

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Veröffentlicht in:	IEEE transactions on signal processing 2010-10, Vol.58 (10), p.5057-5068
1. Verfasser:	Yeredor, Arie
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Asymptotic properties Blind source separation Blinds Blocking Conventions Covariance Covariance matrix Detection, estimation, filtering, equalization, prediction Exact sciences and technology Gaussian Higher order statistics Independent component analysis Information, signal and communications theory Interference Lower bounds Maximum likelihood estimation Miscellaneous nonstationarity Optimization Permission second-order statistics Separation Signal and communications theory Signal processing Signal, noise Source separation Spatial resolution Statistical distributions Telecommunications and information theory time-varying AR processes
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