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Nonlinear parameter estimation of neural network by Gaussian sum

Citace: [] ŠIMANDL, M., HERING, P. Nonlinear parameter estimation of neural network by Gaussian sum. In Proceedings of International Carpathian Control Conference. Košice: Technical University of Košice, 2003. s. 401-404. ISBN: 80-7099-509-2
Druh: STAŤ VE SBORNÍKU
Jazyk publikace: eng
Anglický název: Nonlinear parameter estimation of neural network by Gaussian sum
Rok vydání: 2003
Místo konání: Košice
Název zdroje: Technical University of Košice
Autoři: Miroslav Šimandl , Pavel Hering
Abstrakt EN: 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 estimates comparing to commonly used methods.
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