Performance Bounds for Complex-Valued Independent Vector Analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F20%3A00007818" target="_blank" >RIV/46747885:24220/20:00007818 - isvavai.cz</a>
Alternative codes found
RIV/67985556:_____/20:00531483 RIV/68407700:21340/20:00344852
Result on the web
<a href="https://asap.ite.tul.cz/wp-content/uploads/sites/3/2020/07/Complex_IVA.pdf" target="_blank" >https://asap.ite.tul.cz/wp-content/uploads/sites/3/2020/07/Complex_IVA.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TSP.2020.3009507" target="_blank" >10.1109/TSP.2020.3009507</a>
Alternative languages
Result language
angličtina
Original language name
Performance Bounds for Complex-Valued Independent Vector Analysis
Original language description
Independent Vector Analysis (IVA) is a method for joint Blind Source Separation of multiple datasets with wide area of applications including audio source separation, biomedical data analysis, etc. In this paper, identification conditions and Cramer-Rao Lower Bound (CRLB) on the achievable accuracy are derived for the complex-valued case involving circular and non-circular signals and correlated and uncorrelated datasets. The identification conditions describe when independent sources can be separated from their linear mixture in the statistically consistent manner. The CRLB shows how non-Gaussianty, non-circularity of sources and statistical dependence between datasets influence the attainable separation accuracy. Examples presented in the experimental part confirm the validity of the CRLB. Also, they show certain gap between the attainable accuracy and performance of state-of-the-art algorithms, especially, in case of highly non-circular signals. Hence, there is a room for possible improvements.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
IEEE Transactions on Signal Processing
ISSN
1053-587X
e-ISSN
—
Volume of the periodical
68
Issue of the periodical within the volume
2020
Country of publishing house
US - UNITED STATES
Number of pages
10
Pages from-to
4258-4267
UT code for WoS article
000556759700004
EID of the result in the Scopus database
2-s2.0-85089296542