Blind Source Separation of Single Channel Mixture Using Tensorization and Tensor Diagonalization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00472594" target="_blank" >RIV/67985556:_____/17:00472594 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-53547-0" target="_blank" >http://dx.doi.org/10.1007/978-3-319-53547-0</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-53547-0" target="_blank" >10.1007/978-3-319-53547-0</a>
Alternative languages
Result language
angličtina
Original language name
Blind Source Separation of Single Channel Mixture Using Tensorization and Tensor Diagonalization
Original language description
This paper deals with estimation of structured signals such as damped sinusoids, exponentials, polynomials, and their products from single channel data. It is shown that building tensors from this kind of data results in tensors with hidden block structure which can be recovered through the tensor diagonalization. The tensor diagonalization means multiplying tensors by several matrices along its modes so that the outcome is approximately diagonal or block-diagonal of 3-rd order tensors. The proposed method can be applied to estimation of parameters of multiple damped sinusoids, and their products with polynomial.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10103 - Statistics and probability
Result continuities
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)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Latent Variable Analysis and Signal Separation, 13th International Conference, LVA/ICA 2017
ISBN
978-3-319-53546-3
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
11
Pages from-to
36-46
Publisher name
Springer
Place of publication
Cham
Event location
Grenoble
Event date
Feb 21, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000418581400004