Fuzzy Neural Networks on Embedded platforms

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F17%3AA0000131" target="_blank" >RIV/47813059:19240/17:A0000131 - isvavai.cz</a>
Result on the web
<a href="http://irafm.osu.cz/cjs2017/materials/cjs2017proceedings.pdf" target="_blank" >http://irafm.osu.cz/cjs2017/materials/cjs2017proceedings.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Fuzzy Neural Networks on Embedded platforms
Original language description
Fuzzy modeling is the method that describes a behavior of real systems using the fuzzy logic and the fuzzy reasoning. However, in cases when the need for real-time control of the process in embedded systems behavior arises, a standard HW platforms such as personal computers or the ARM platforms are not suitable regarding their limited performance. Additionally, there are many cases in which the conventional approaches fail due to nonlinear system behavior. The afore mentioned is the reason of involving state-of-the-art technologies such as the FPGAs and the Fuzzy Neural Networks into the chain of modeling. The Takagi-Sugeno fuzzy non-linear regression model is also one of the suitable Artificial Intelligence means for fuzzy modeling.
Czech name
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Czech description
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Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
PROCEEDINGS OF THE 20TH CZECH-JAPAN SEMINAR ON DATA ANALYSIS AND DECISION MAKING UNDER UNCERTAINTY
ISBN
9788074649325
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
25-33
Publisher name
University of Ostrava
Place of publication
Ostrava
Event location
Pardubice
Event date
Jan 1, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000418391500003

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