Wavelet based dictionaries for dimensionality reduction of ECG signals
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24510%2F19%3A00007355" target="_blank" >RIV/46747885:24510/19:00007355 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S1746809419301739" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1746809419301739</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.bspc.2019.101593" target="_blank" >10.1016/j.bspc.2019.101593</a>
Alternative languages
Result language
angličtina
Original language name
Wavelet based dictionaries for dimensionality reduction of ECG signals
Original language description
Dimensionality reduction of ECG signals is considered within the framework of sparse representation. The approach constructs the signal model by selecting elementary components from a redundant dictionary via a greedy strategy. The proposed wavelet dictionaries are built from the multiresolution scheme, but translating the prototypes within a shorter step than that corresponding to the wavelet basis. The reduced representation of the signal is shown to be suitable for compression at low level distortion. In that regard, compression results are superior to previously reported benchmarks on the MIT-BIH Arrhythmia data set.
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
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Biomedical Signal Processing and Control
ISSN
1746-8094
e-ISSN
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Volume of the periodical
54
Issue of the periodical within the volume
SEP 2019
Country of publishing house
GB - UNITED KINGDOM
Number of pages
9
Pages from-to
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UT code for WoS article
000488140200007
EID of the result in the Scopus database
2-s2.0-85068436096