Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
Natural gradient works efficiently in learning
Neural Computation
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
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This paper presents a method for blind identification of a system whose transfer matrix is non-invertible at infinity, based on independent component analysis. In the proposed scheme, the transfer matrix to be identified is pre-multiplied by an appropriate polynomial matrix, named interactor, in order to compensate the row relative degrees and obtain a biproper system. It is then pre-multiplied by a demixing matrix via an existing approximate method. Both of these matrices are estimated blindly, i.e. with the input signals being unknown. The identified system is thus obtained as the inverse of the multiplication of these matrices.