Performance Bound for Blind Extraction of Non-gaussian Complex-valued Vector Component from Gaussian Background

dc.contributor.authorKautský, Václav
dc.contributor.authorKoldovský, Zbyněk
dc.contributor.authorTichavský, Petr
dc.date.accessioned2019-08-06T06:45:49Z
dc.date.available2019-08-06T06:45:49Z
dc.date.issued2019-01-01
dc.description.abstractIndependent Vector Extraction aims at the joint blind source extraction of K dependent signals of interest (SOI) from K mixtures (one signal from one mixture). Similarly to Independent Component/Vector Analysis (ICA/IVA), the SOIs are assumed to be independent of the other signals in the mixture. Compared to IVA, the (de-)mixing IVE model is reduced in the number of parameters for the extraction problem. The SOIs are assumed to be non-Gaussian or noncircular Gaussian, while the other signals are modeled as circular Gaussian. In this paper, a Cramér-Rao-Induced Bound (CRIB) for the achievable Interference-to-Signal Ratio (ISR) is derived for IVE. The bound is compared with similar bounds for ICA, IVA, and Independent Component Extraction (ICE). Numerical simulations show a good correspondence between the empirical results and the theory.cs
dc.format.extent5 strancs
dc.identifier.doi10.1109/ICASSP.2019.8683885
dc.identifier.urihttps://dspace.tul.cz/handle/15240/153080
dc.identifier.urihttps://ieeexplore.ieee.org/document/8683885
dc.language.isocscs
dc.relation.ispartofICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
dc.subjectBlind Source Extractioncs
dc.subjectIndependent Component Analysiscs
dc.subjectIndependent Vector Analysiscs
dc.subjectCramer-Rao Boundcs
dc.titlePerformance Bound for Blind Extraction of Non-gaussian Complex-valued Vector Component from Gaussian Backgroundcs
dc.typeConference Paper
local.article.number8683885
local.citation.epage5291
local.citation.spage5287
local.event.edate2019-05-17
local.event.locationBrighton Conference CentreBrighton; United Kingdom
local.event.sdate2019-05-12
local.event.title44th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2019
local.relation.volume2019-May, May 2019
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