A1 Refereed original research article in a scientific journal
Minimum Distance Index for BSS, Generalization, Interpretation and Asymptotics
Authors: Niko Lietzén, Joni Virta, Klaus Nordhausen, Pauliina Ilmonen
Publisher: AUSTRIAN STATISTICAL SOC
Publication year: 2020
Journal: Austrian Journal of Statistics
Journal name in source: AUSTRIAN JOURNAL OF STATISTICS
Journal acronym: AUST J STAT
Volume: 49
Issue: 4
First page : 57
Last page: 68
Number of pages: 12
ISSN: 1026-597X
DOI: https://doi.org/10.17713/ajs.v49i4.1130
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/47792409
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.
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