Please use this identifier to cite or link to this item:
https://elib.bsu.by/handle/123456789/233338| Title: | Minimum distance index for non-square complex valued mixing matrices |
| Authors: | Lietzen, N. Virta, J. Nordhausen, K. Ilmonen, P. |
| Keywords: | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Математика ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Кибернетика |
| Issue Date: | 2019 |
| Publisher: | Minsk : BSU |
| Citation: | Computer Data Analysis and Modeling: Stochastics and Data Science : Proc. of the Twelfth Intern. Conf., Minsk, Sept. 18-22, 2019. – Minsk : BSU, 2019. – P. 79-86. |
| Abstract: | We consider complex valued linear blind source separation, where the objective is to estimate a subset of the latent sources. 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 square real valued (original) case. |
| URI: | http://elib.bsu.by/handle/123456789/233338 |
| ISBN: | 978-985-566-811-5 |
| Sponsorship: | N. Lietzen gratefully acknowledges financial support from the Emil Aaltonen Foundation (grant 180144). The authors would also like to thank the anonymous referee. |
| Appears in Collections: | 2019. Computer Data Analysis and Modeling : Stochastics and Data Science |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.