Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Three easy ways for separating nonlinear mixtures?
Signal Processing - Special issue on independent components analysis and beyond
MISEP - Linear and nonlinear ICA based on mutual information
The Journal of Machine Learning Research
Blind source separation of a class of nonlinear mixtures
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Kernel-based nonlinear independent component analysis
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Source separation in post-nonlinear mixtures
IEEE Transactions on Signal Processing
A generic framework for blind source separation in structurednonlinear models
IEEE Transactions on Signal Processing
Blind separation of mixture of independent sources through aquasi-maximum likelihood approach
IEEE Transactions on Signal Processing
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This paper deals with nonlinear Blind Source Separation (BSS) applied to a simple bijective "toy" model. Our objective is to better understand the difficulties encountered in nonlinear BSS, especially when estimating the parameters of mixing or separating structures. The results of this study and the proposed solutions may then be used by the BSS researchers dealing with actual nonlinear physical models. The simulation results confirm the usefulness of our proposed solutions.