Next: EM-algorithm for Independent Component
Up: Fast Algorithms for Bayesian
Previous: Fast Algorithms for Bayesian
We consider the problem of finding linearly mixed source signals
from observed noisy linear mixtures
The mixing matrix A is unknown and
n(t) is additive noise.
When we consider a finite number of observed mixture samples, we may write the data model in matrix form as
Each time-indexed matrix contains a sequence of vector samples, e.g.
To find the mixing matrix A, it is necessary that the source
signals possess certain statistical properties. For example, it is
sufficient that the source signals are not Gaussian. It is also
sufficient that the possibly Gaussian sources have time dependencies, together with some