Paper data
Title:
Blind Identifiability of Class of Nonlinear Instantaneous ICA Models Author(s): Erikson Jan, Signal Processing Laboratory, Helsinki University of Technology, Finland Koivunen Visa, Signal Processing Laboratory, Helsinki University of Technology, Finland Page numbers in the proceedings: Volume II pp 7-10 Session: Blind Source Separation / Independent Component Analysis (2/2)
Paper abstract
The identifiability/separability of nonlinear instantaneous ICA models is considered. The identifiability proof is constructed for the class of nonlinearities satisfying addition theorem. Addition theorem covers wide variety of nonlinear mixing systems of engineering interest. An algorithm for separating such nonlinear mixtures is presented and the feasibility of the approach is demonstrated.
Paper
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