Title :
Natural gradient algorithm for blind separation of overdetermined mixture with additive noise
Author :
Zhang, L.-Q. ; Cichocki, A. ; Amari, S.
Author_Institution :
RIKEN, Inst. of Phys. & Chem. Res., Saitama, Japan
Abstract :
We study the natural gradient approach to blind separation of overdetermined mixtures. First we introduce a Lie group on the manifold of overdetermined mixtures, and endow a Riemannian metric on the manifold based on the property of the Lie group. Then we derive the natural gradient on the manifold using the isometry of the Riemannian metric. Using the natural gradient, we present a new learning algorithm based on the minimization of mutual information.
Keywords :
array signal processing; gradient methods; information theory; learning systems; matrix algebra; minimisation; noise; Lie group; Riemannian metric isometry; additive noise; blind separation; learning algorithm; manifold; mixing matrix; mutual information minimization; natural gradient algorithm; overdetermined mixture; sensor signals; Additive noise; Biomedical signal processing; Biosensors; Blind source separation; Image enhancement; Minimization methods; Mutual information; Signal processing algorithms; Standards development; Vectors;
Journal_Title :
Signal Processing Letters, IEEE