Minimum Distance Index for BSS, Generalization, Interpretation and Asymptotics

Authors

  • Niko Lietzén Aalto University, School of Science
  • Joni Virta Aalto University, School of Science; University of Turku
  • Klaus Nordhausen Institute of Statistics & Mathematical Methods in Economics, Vienna University of Technology
  • Pauliina Ilmonen Aalto University, School of Science

DOI:

https://doi.org/10.17713/ajs.v49i4.1130

Abstract

We consider complex valued linear blind source separation, where the signal dimension might be smaller than the dimension of the observable data vector. In order to measure the success of the signal separation, we propose an extension of the minimum distance index and establish its properties. Interpretations for the index are derived through connections to signal-to-noise ratios and correlations. The interpretations are novel also for the real valued original case. In addition, we consider the asymptotic behavior of the extended minimum distance index. This paper is an invited extended version of the paper presented at the CDAM 2019 conference.

Downloads

Published

2020-04-13

How to Cite

Lietzén, N., Virta, J., Nordhausen, K., & Ilmonen, P. (2020). Minimum Distance Index for BSS, Generalization, Interpretation and Asymptotics. Austrian Journal of Statistics, 49(4), 57–68. https://doi.org/10.17713/ajs.v49i4.1130

Issue

Vol. 49 No. 4 (2020): Special Issue CDAM 2019

Section

Special Issue CDAM conference

License

Copyright (c) 2020 Austrian Journal of Statistics

Creative Commons License

This work is licensed under a Creative Commons Attribution 3.0 Unported License.

The Austrian Journal of Statistics publish open access articles under the terms of the Creative Commons Attribution (CC BY) License. 

The Creative Commons Attribution License (CC-BY) allows users to copy, distribute and transmit an article, adapt the article and make commercial use of the article. The CC BY license permits commercial and non-commercial re-use of an open access article, as long as the author is properly attributed.

Copyright on any research article published by the Austrian Journal of Statistics is retained by the author(s). Authors grant the Austrian Journal of Statistics a license to publish the article and identify itself as the original publisher. Authors also grant any third party the right to use the article freely as long as its original authors, citation details and publisher are identified.

 

Manuscripts should be unpublished and not be under consideration for publication elsewhere. By submitting an article, the author(s) certify that the article is their original work, that they have the right to submit the article for publication, and that they can grant the above license.