A "nonnegative PCA" algorithm for independent component analysis

MD, Plumbley; E, Oja

doi:10.1109/tnn.2003.820672

Public

A "nonnegative PCA" algorithm for independent component analysis.

Published in IEEE transactions on neural networks • Jan 1, 2004

Authors:

Plumbley MD

,

Oja E

Abstract

We consider the task of independent component analysis when the independent sources are known to be nonnegative and well-grounded, so that they have a nonzero probability density function (pdf) in the region of zero. We propose the use of a "nonnegative principal component analysis (nonnegative PCA)...

Discussions