ICA by Tensorial Methods
Aapo Hyvärinen, Juha Karhunen, Erkki Oja · 2001
An approach to ICA estimation that is rather different from those in the previous chapters is given by tensorial methods. The fourth-order cumulants of mixtures give all the fourth-order information inherent in the data. They can be used to define a tensor, which is a generalization of the covariance matrix. Then we can apply eigenvalue decomposition on this matrix. The eigenvectors more or less directly give the mixing matrix for whitened data.