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|Title: ||Kurtosis approach nonlinear blind source seperation|
|Authors: ||Duong, Vu A.|
Stubbemd, Allen R.
|Keywords: ||independent component analysis|
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.|
|Appears in Collections:||JPL TRS 1992+|
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