Common components analysis via linked blind source separation

Guoxu Zhou; Andrzej Cichocki; Danilo P. Mandic

ICASSP 2015accepted0 citations

Common components analysis via linked blind source separation

Guoxu Zhou, Andrzej Cichocki, Danilo P. Mandic

Abstract

Very often data we encounter in practice is a collection of matrices rather than a single matrix. These multi-block data often share some common features, due to the background in which they are measured. In this study we propose a new concept of linked blind source separation (BSS) that aims at discovering and extracting unique and physically meaningful common components from multi-block data, which also contain strong individual components. The validity and potential of the proposed method is justified by simulations.

BibTeX

@inproceedings{icassp2015_commoncomponents,
  title = {Common components analysis via linked blind source separation},
  author = {Guoxu Zhou and Andrzej Cichocki and Danilo P. Mandic},
  booktitle = {ICASSP 2015},
  year = {2015}
}