Nonlinear Independent Component Analysis Using Ensemble Learning: Theory
نویسنده
چکیده
A nonlinear version of independent component analysis is presented. The mapping from sources to observations is modelled by a multi-layer perceptron network and the distributions of sources are modelled by mixtures of Gaussians. The posterior probability of all the unknown parameters is estimated by ensemble learning. In this paper, we present the theory of the method, and in a companion paper experimental results.
منابع مشابه
Nonlinear Independent Component Analysis Using Ensemble Learning: Experiments and Discussion
In this paper, we present experimental results on a non-linear independent component analysis approach based on Bayesian ensemble learning. The theory of the method is discussed in a companion paper. Simulations with artiicial and natural data demonstrate the feasibility and good performance of the proposed approach. We also discuss the relationships of the method to other existing methods.
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