On-line identifikace neuronovou sítí s použitím algoritmů Levenberg-Marquardt a Back-propagation

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F04%3APU41335" target="_blank" >RIV/00216305:26220/04:PU41335 - isvavai.cz</a>
Výsledek na webu
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DOI - Digital Object Identifier
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Jazyk výsledku
angličtina
Název v původním jazyce
On-line Identification Based on Neural Networks using of Levenberg-Marquardt Method and Back-propagation Algorithm
Popis výsledku v původním jazyce
In order to be able to control a system by means of an automatically adaptable controller, we have to adjust its parameters to the changes taking place in the system. For this purpose a number of methods have been developed. A frequently used identification method is the least-squares method, but we are limited by the choice of the suitable sampling period. The neural network seems to be a desirable solution because of its adaptation characteristics. Among the most used learning algorithms belong thhe Levenberg- Marquardt and back-propagation.
Název v anglickém jazyce
On-line Identification Based on Neural Networks using of Levenberg-Marquardt Method and Back-propagation Algorithm
Popis výsledku anglicky
In order to be able to control a system by means of an automatically adaptable controller, we have to adjust its parameters to the changes taking place in the system. For this purpose a number of methods have been developed. A frequently used identification method is the least-squares method, but we are limited by the choice of the suitable sampling period. The neural network seems to be a desirable solution because of its adaptation characteristics. Among the most used learning algorithms belong thhe Levenberg- Marquardt and back-propagation.

Rok uplatnění
2004
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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