Modeling of EEG Signal with Homeostatic Neural Network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21260%2F13%3A00226437" target="_blank" >RIV/68407700:21260/13:00226437 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Modeling of EEG Signal with Homeostatic Neural Network
Original language description
Artificial neural networks have the ability to model signals and predict values that are complex and for which an explicit representation is not known. Therefore, it is a convenient method for modeling of electroencephalograph due to the easiness of acquiring large data sets and a great difficulty to interpret the signals. The growth of computational power in connection with the intensification of the knowledge of biological neural networks open new possibilities for signal modelling.
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
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Nostradamus 2013: Prediction, Modeling and Analysis of Complex Systems
ISBN
978-3-319-00541-6
ISSN
2194-5357
e-ISSN
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Number of pages
6
Pages from-to
175-180
Publisher name
Springer
Place of publication
Heidelberg
Event location
Ostrava
Event date
Jun 3, 2013
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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