Multivariate Gaussianization for Data Processing
Multivariate Gaussianization for Data Processing
Multivariate Gaussianization for Data Processing
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Intro Iterative <strong>Gaussianization</strong> Experiments ConclusionsPreliminariesDefinition 2: Iterative <strong>Gaussianization</strong> Trans<strong>for</strong>mGiven a d-dimensional random variable x (0) = [x 1, . . . , x d ] ⊤ with PDF p(x (0) ),in each iteration k, a two-step processing is per<strong>for</strong>med:G : x (k+1) = R (k) Ψ (k) (x (k) )whereΨ (k) is the marginal <strong>Gaussianization</strong> of each dimension of x (k) <strong>for</strong> thecorresponding iteration,R (k) is a rotation matrix <strong>for</strong> the marginally Gaussianized variable Ψ (k) (x (k) ).