Copula component analysis

Authors:
Jian Ma;Zengqi Sun
Affiliations:
Department of Computer Science, Tsinghua University, Beijing, China;Department of Computer Science, Tsinghua University, Beijing, China
Venue:
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Year:
2007

Citing 7
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Abstract

A framework named copula component analysis (CCA) for blind source separation is proposed as a generalization of independent component analysis (ICA). It differs from ICA which assumes independence of sources that the underlying components may be dependent by certain structure which is represented by Copula. By incorporating dependency structure, much accurate estimation can be made in principle in the case that the assumption of independence is invalidated. A two phrase inference method is introduced for CCA which is based on the notion of multi-dimensional ICA. Simulation experiments preliminarily show that CCA can recover dependency structure within components while ICA does not.