Independent Component Analysis (ICA) and Method of Estimating Functions (5th Workshop on Stochastic Numerics)
Шун-ичи Амари · Institutional Repositories DataBase (IRDB) · 2001
Independent component analysis (ICA) is anew method of extracting inde- pendent components from multivariate data.It can be applied to various fields such as vision and auditory signal analysis, communication systems, and biomedical and brain engineering.There have been proposed anumber of algorithms.The present article shows that most of them use estimating functions from the statistical point of view, and give aunified theory, based on information geometry, to elucidate the efficiency and stability of the algorithms.This gives new efficient adaptive algorithms useful for various problems.