Computational performance of the parameters estimation in extreme seeking entropy algorithm

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F20%3A43921330" target="_blank" >RIV/60461373:22340/20:43921330 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9232875" target="_blank" >https://ieeexplore.ieee.org/document/9232875</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.23919/AE49394.2020.9232875" target="_blank" >10.23919/AE49394.2020.9232875</a>

Result language
angličtina
Original language name
Computational performance of the parameters estimation in extreme seeking entropy algorithm
Original language description
This paper is dedicated to the evaluation of the computational time performance of the algorithms that estimate the parameters of the generalized Pareto distribution, namely Method of Moments, Maximum likelihood estimator and Quasi-maximum likelihood algorithms. The generalized Pareto distribution is utilized by the Extreme Seeking Entropy algorithm to detect novelty in data. The algorithm is evaluating the weight increments of the simple adaptive filter that are obtained via incrementally learning algorithm. The computational time performance is examined in the experiment with the detection of step-change parameters of the signal generator. Its output contains also additive Gaussian noise. © 2020 University of West Bohemia.
Czech name
—
Czech description
—

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
25th International Conference on Applied Electronics, AE 2020
ISBN
978-80-261-0891-7
ISSN
1803-7232
e-ISSN
1805-9597
Number of pages
4
Pages from-to
—
Publisher name
IEEE Computer Society
Place of publication
Los Alamitos
Event location
Plzeň
Event date
Aug 8, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000659296200039

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