Alzheimer disease diagnostics from EEG via Wishart distribution of fractional processes
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F21%3A00353487" target="_blank" >RIV/68407700:21340/21:00353487 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/s11760-021-01875-9" target="_blank" >https://doi.org/10.1007/s11760-021-01875-9</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11760-021-01875-9" target="_blank" >10.1007/s11760-021-01875-9</a>
Alternative languages
Result language
angličtina
Original language name
Alzheimer disease diagnostics from EEG via Wishart distribution of fractional processes
Original language description
Exact estimation of Hurst exponent from a signal is a complex task that determines the fractional character of the investigated sample. In this work, we propose a maximum likelihood technique using Wishart distribution and autocorrelation structure of the investigated time series. Unlike conventional methods, we perform signal segmentation and use the aggregated data to obtain an unbiased estimate of Hurst exponent. The efficiency of the estimation is validated by four different methods of fractional Brownian motion generation. The resulting estimates have very tiny confidence intervals as well as small mean square error. Additionally, the proposed methodology has been applied to 19-channel EEG time series and their Hurst exponent estimation related to the diagnostics of Alzheimer's disease.
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
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
SIGNAL IMAGE AND VIDEO PROCESSING
ISSN
1863-1703
e-ISSN
1863-1711
Volume of the periodical
15
Issue of the periodical within the volume
7
Country of publishing house
GB - UNITED KINGDOM
Number of pages
8
Pages from-to
1435-1442
UT code for WoS article
000627659700001
EID of the result in the Scopus database
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