Evolutionary Weighted Ensemble for EEG Signal Recognition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F14%3A86089795" target="_blank" >RIV/61989100:27740/14:86089795 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-07773-4_20" target="_blank" >http://dx.doi.org/10.1007/978-3-319-07773-4_20</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-07773-4_20" target="_blank" >10.1007/978-3-319-07773-4_20</a>
Alternative languages
Result language
angličtina
Original language name
Evolutionary Weighted Ensemble for EEG Signal Recognition
Original language description
Recognition of EEG signal is very complex but very important problem. In this paper we focus on simplified classification problem which consists of detection finger movement based on analysis of seven EEG sensors. Signal gathered by each sensor are subsequently classified by respective classification algorithm which is based on data compression and so called LZ-Complexity. To improve the overall accuracy of the system, Evolutionary Weighted Ensemble (EWE) system is proposed. Parameters of the EWE are set in learning procedure which uses tailored for that purpose evolutionary algorithm. To take full advantage of information returned sensor classifiers, setting negative weights are permitted, which significantly elevates overall accuracy. Evaluation of EWE and its comparison against selected classical ensemble algorithm are carried on empirical data consisting of almost 5 hundred samples. The results shows that EWE algorithm exploits knowledge represented by sensor classifiers very effec
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Intelligent Systems and Computing. Volume 298
ISBN
978-3-319-07772-7
ISSN
2194-5357
e-ISSN
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Number of pages
10
Pages from-to
201-210
Publisher name
Springer
Place of publication
Heidelberg
Event location
Shenzhen
Event date
Jun 13, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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