Fast approximation of nonlinearities for improving inversion algorithms of PNL mixtures and Wiener systems

Signal Processing

Volumn 85, Issue 9, 2005, Pages 1780-1786

  Sole Casals J ^a   Jutten, C ^b   Pham, D T ^c  

^a UNIVERSITY OF VIC CENTRAL UNIVERSITY OF CATALONIA   (Spain)

^b GRENOBLE INSTITUTE OF TECHNOLOGY   (France)

^c CNRS   (France)

Author keywords

Nonlinear ICA; Nonlinear source separation; Wiener systems

Indexed keywords

ALGORITHMS; BLIND SOURCE SEPARATION; COMPUTATIONAL COMPLEXITY; MATHEMATICAL MODELS; PARAMETER ESTIMATION; RANDOM PROCESSES; SIGNAL PROCESSING;

NONLINEAR ICA; NONLINEAR SOURCE SEPARATION; POST-NONLINEAR (PNL) MIXTURE; WIENER SYSTEMS;

NONLINEAR SYSTEMS;

EID: 21744439355     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2004.11.030     Document Type: Article

References (11)

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