Non-linear adaptive systems
Lars Kai Hansen
Department of Informatics and Mathematical Modelling,
Building 321, Technical University of Denmark,
2800 Kongens Lyngby, Denmark
Non-linearity is essential to some adaptive systems.
So-called independent component analysis (ICA) for
reconstruction of random source signals from linear mixtures, is
a prominent example. Using linear systems it is only possible
to recover the subspace spanned by the columns of the mixing
matrix, while a broad class of non-linearities allow full
recovery of both the unknown mixing matrix and the source
signals, ie., blind signal separation.
I will discuss recent progress in our understanding of
the ICA problem based on mean field methods and linear