V-shaped neurons in hidden layer of ANN universal approximator without flat domains
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F16%3A00305215" target="_blank" >RIV/68407700:21220/16:00305215 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21340/16:00305215
Result on the web
<a href="http://ieeexplore.ieee.org/document/7727229/" target="_blank" >http://ieeexplore.ieee.org/document/7727229/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/IJCNN.2016.7727229" target="_blank" >10.1109/IJCNN.2016.7727229</a>
Alternative languages
Result language
angličtina
Original language name
V-shaped neurons in hidden layer of ANN universal approximator without flat domains
Original language description
A three-layer perceptron ANN is designed to avoid difficulties during learning process. The resulting V-shaped Artificial Neural Network has universal approximation property and its learning is based on the minimization of least squares sum. The main advantage of this approach is in the absence of flat domains with a small norm of objective function gradie"nt.
Czech name
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Czech description
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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
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2016
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 International Joint Conference on Neural Networks 2016
ISBN
9781509006199
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
419-425
Publisher name
IEEE
Place of publication
New York
Event location
Vancouver
Event date
Jul 24, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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