Nonlinear identification based on RBF neural network

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F11%3APU94690" target="_blank" >RIV/00216305:26220/11:PU94690 - 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 identification based on RBF neural network

Original language description

This article is focused on the off-line identification of nonlinear dynamic systems. Hammerstein model was used for this identification. RBF (Radial Basis Function) neural network is used here to approximate the input nonlinear static function. This network is implemented as a piecewise linear function.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BC - Theory and management systems

OECD FORD branch

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Project

<a href="/en/project/GA102%2F09%2F1680" target="_blank" >GA102/09/1680: Control Algorithm Design by Means of Evolutionary Approach</a><br>

Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2011

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

DAAAM International Scientific Book

ISSN

1726-9687

e-ISSN

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Volume of the periodical

10

Issue of the periodical within the volume

11

Country of publishing house

AT - AUSTRIA

Number of pages

8

Pages from-to

547-554

UT code for WoS article

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EID of the result in the Scopus database

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