Nonlinear parameter estimation of neural network by Gaussian sum

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F03%3A00000018" target="_blank" >RIV/49777513:23520/03:00000018 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Nonlinear parameter estimation of neural network by Gaussian sum
Original language description
Aim of the paper is to describe a new approach for the neural network parameter estimation of a nonlinear stochastic system. The mathematical model of the system created by the multilayer perceptron neural network is based on measured data exclusively assuming no or only diminutive knowledge about physics of the system. The paraters called weights in neural networks are estimated by nonlinear estimation method using Gaussian sum approach. The new optimization approach yields better parameter estimatescomparing to commonly used methods.
Czech name
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Czech description
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Project
<a href="/en/project/GA102%2F01%2F0021" target="_blank" >GA102/01/0021: Nonlinear estimation and change detection for stochastic systems</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2003
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of International Carpathian Control Conference
ISBN
80-7099-509-2
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
401-404
Publisher name
Technical University of Košice
Place of publication
Košice
Event location
Tatranská Lomnica
Event date
May 26, 2003
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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