Introduction - If you have any usage issues, please Google them yourself
Source separation of complex signals with JADE.
Jade performs `Source Separation in the following sense:
X is an n x T data matrix assumed modelled as X = A S+ N where
o A is an unknown n x m matrix with full rank.
o S is a m x T data matrix (source signals) with the properties
a) for each t, the components of S(:,t) are statistically
independent
b) for each p, the S(p,:) is the realization of a zero-mean
`source signal .
c) At most one of these processes has a vanishing 4th-order
cumulant.
o N is a n x T matrix. It is a realization of a spatially white
Gaussian noise, i.e. Cov(X) = sigma*eye(n) with unknown variance
sigma. This is probably better than no modeling at all...