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タイトルKurtosis Approach for Nonlinear Blind Source Separation
著者(英)Duong, Vu A.; Stubbemd, Allen R.
著者所属(英)Jet Propulsion Lab., California Inst. of Tech.
発行日2005-12-14
言語eng
内容記述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.
NASA分類Communications and Radar
権利Copyright


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