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Please use this identifier to cite or link to this item: http://hdl.handle.net/2014/41344

Title: Kurtosis approach nonlinear blind source seperation
Authors: Duong, Vu A.
Stubbemd, Allen R.
Keywords: independent component analysis
kurtosis
higher order statistics
Issue Date: 14-Dec-2005
Publisher: Pasadena, CA : Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2005.
Citation: InTech '05, Phu Ket, Thailand, December 14-16, 2005.
Abstract: In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation.
URI: http://hdl.handle.net/2014/41344
Appears in Collections:JPL TRS 1992+

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