AN ELECTRIC FIELD APPROACH TO INDEPENDENT COMPONENT ANALYSIS
Sepp Hochreiter and Michael C. Mozer
fhochreit,mozerg@cs.colorado.edu
We propose a novel algorithm for Independent Compo-
nent Analysis (ICA) that is based on an electric eld
metaphor. As with all ICA techniques, the algorithm
searches for a demixing model that produces compo-
nents whose joint distribution matches the factorial
distribution (i.e., the product of the marginal distri-
butions). The joint and factorial distributions are rep-
resented as positively and negatively charged particles,
respectively, and the dynamics of the search are based
on the interactions among particles. The algorithm can
deal with arbitrary distributions for the sources, non-
linear mixing functions, noisy observations, and an un-
equal number of source and mixture components. The
limitation of the algorithm is that it does not scale with
the number of sources. Nonetheless, we demonstrate
that the algorithm can solve challenging ICA problems
that are beyond the capabilities of other ICA methods.