Neural Network Representation of Fuzzy Systems
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41110%2F06%3A15044" target="_blank" >RIV/60460709:41110/06:15044 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
čeština
Original language name
Representace fuzzy systémů neuronovými sítěmi
Original language description
Fuzzy systems are sometimes represented in a neural network form as so called neuro-fuzzy systems so that the neural network adaptation algorithms might be used for their fine-tuning to a concrete application. A neuro-fuzzy system is a group of mutuallyconnected simple processing units. However, it does not come under paradigm of fuzzy neural network, which is a group of fuzzy neurons connected in a way commonly used in neural network theory. In the article we will show how Mamdani fuzzy systems and zero-order or first-order Sugeno fuzzy systems might be represented with fuzzy neural networks. Fuzzy neural network representations of Sugeno fuzzy systems contain only real neurons. Only a special type of Sugeno fuzzy systems may be represented with a classical neural networks. However, Sugeno fuzzy systems may be with classical neural networks approximated.
Czech name
Representace fuzzy systémů neuronovými sítěmi
Czech description
Fuzzy systems are sometimes represented in a neural network form as so called neuro-fuzzy systems so that the neural network adaptation algorithms might be used for their fine-tuning to a concrete application. A neuro-fuzzy system is a group of mutuallyconnected simple processing units. However, it does not come under paradigm of fuzzy neural network, which is a group of fuzzy neurons connected in a way commonly used in neural network theory. In the article we will show how Mamdani fuzzy systems and zero-order or first-order Sugeno fuzzy systems might be represented with fuzzy neural networks. Fuzzy neural network representations of Sugeno fuzzy systems contain only real neurons. Only a special type of Sugeno fuzzy systems may be represented with a classical neural networks. However, Sugeno fuzzy systems may be with classical neural networks approximated.
Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2006
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 10th IASTED International Conference on Artifitial Intelligence and Soft Computing
ISBN
0-88986-610-4
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
221-229
Publisher name
ACTA Press
Place of publication
Calgary, Zurich
Event location
Palma de Mallorca
Event date
Aug 28, 2006
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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