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Communication Dans Un Congrès Année : 2017

Blind compensation of polynomial mixtures of Gaussian signals with application in nonlinear blind source separation

Résumé

In this paper, a proof is provided to show that Gaussian signals will lose their Gaussianity if they are passed through a polynomial of an order greater than 1. This can help in blind compensation of polynomial nonlinearities on Gaussian sources by forcing the output to follow a Gaussian distribution (the term " blind " refers to lack of any prior information about the nonlinear function). It may have many applications in different fields of nonlinear signal processing for removing the nonlinearity. Particularly, in nonlinear blind source separation , it can be used as a pre-processing step to transform the problem to a linear one, which is already well studied in the literature. This idea is proposed, proved, and finally verified by a simple simulation as a proof of concept in this paper.
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Dates et versions

hal-01552278 , version 1 (01-07-2017)

Identifiants

Citer

Bahram Ehsandoust, Bertrand Rivet, Massoud Babaie-Zadeh, Christian Jutten. Blind compensation of polynomial mixtures of Gaussian signals with application in nonlinear blind source separation. ICASSP 2017 - IEEE International Conference on Acoustics, Speech and Signal Processing, Mar 2017, New Orleans, United States. pp.4681 - 4685, ⟨10.1109/ICASSP.2017.7953044⟩. ⟨hal-01552278⟩
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