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Citation

Hering, P. : Gaussian sum based methods for neural network parameters estimation: aspects and comparison . Controlo 2006, p. 1-6, Instituto Superior Tecnico, Lisbon, 2006.

Abstract

Parameter estimation of a multi-layer perceptron network using global nonlinear filtering methods is treated. The truncated second-order filter is applied within the framework of the Gaussian sum approach to design the truncated second-order Gaussian sum filter and it is pointed out, that the filter has significantly less computational demands than the sigma point Gaussian sum filter if it is used for the parameter estimation of multi-layer perceptron network. Further, the Gaussian sum based estimators such as the Gaussian sum filter, the sigma point Gaussian sum filter and the truncated second-order Gaussian sum filter are compared in a numerical example.

Detail of publication

Title: Gaussian sum based methods for neural network parameters estimation: aspects and comparison
Author: Hering, P.
Language: English
Date of publication: 11 Sep 2006
Year: 2006
Type of publication: Papers in proceedings of reviewed conferences
Title of journal or book: Controlo 2006
Page: 1 - 6
Publisher: Instituto Superior Tecnico
Address: Lisbon
Date: 11 Sep 2006 - 13 Sep 2006
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Keywords

Parameter estimation, nonlinear filter, global optimisation, probability density function, neural network

BibTeX

@INPROCEEDINGS{HeringP_2006_Gaussiansumbased,
 author = {Hering, P.},
 title = {Gaussian sum based methods for neural network parameters estimation: aspects and comparison},
 year = {2006},
 publisher = {Instituto Superior Tecnico},
 journal = {Controlo 2006},
 address = {Lisbon},
 pages = {1-6},
 url = {http://www.kky.zcu.cz/en/publications/HeringP_2006_Gaussiansumbased},
}