Orthogonally-Constrained Extraction of Independent Non-Gaussian Component from Non-Gaussian Background without ICA

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24220%2F18%3A00006128" target="_blank" >RIV/46747885:24220/18:00006128 - isvavai.cz</a>
Alternative codes found
RIV/67985556:_____/18:00492879
Result on the web
<a href="https://asap.ite.tul.cz/wp-content/uploads/sites/3/2018/05/LVA2018v2.pdf" target="_blank" >https://asap.ite.tul.cz/wp-content/uploads/sites/3/2018/05/LVA2018v2.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-93764-9_16" target="_blank" >10.1007/978-3-319-93764-9_16</a>

Result language
angličtina
Original language name
Orthogonally-Constrained Extraction of Independent Non-Gaussian Component from Non-Gaussian Background without ICA
Original language description
We propose a new algorithm for Independent ComponentExtraction that extracts one non-Gaussian component and is capable to exploit the non-Gaussianity of background signals without decomposing them into independent components. The algorithm is suitable for situations when the signal to be extracted is determined through initialization; it shows an extra stable convergence when the target componentis dominant. In simulations, the proposed method is compared with Natural Gradient and One-unit FastICA, and it yields improved results interms of the Signal-to-Interference ratio and the number of successful extractions.
Czech name
—
Czech description
—

Project
<a href="/en/project/GA17-00902S" target="_blank" >GA17-00902S: Advanded Joint Blind Source Separation Methods</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) - 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018
ISBN
9783319937632
ISSN
03029743
e-ISSN
—
Number of pages
10
Pages from-to
161-170
Publisher name
—
Place of publication
Velká Británie
Event location
Guildford, UK
Event date
Jan 1, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—

Similar results(10)