Recurrent Neural Networks for Non-linear System Identification

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F99%3A00000034" target="_blank" >RIV/00216305:26210/99:00000034 - 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

Recurrent Neural Networks for Non-linear System Identification

Original language description

The contribution shows Elman neural network used for non-linear system identification. A simple example of non-linear dynamic system is used to test the performance of networks with different number of hidden units. Results shows that higher number of hidden neurons surprisingly degrades the performance of the network both in training and generalisation abilities.

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

JD - Use of computers, robotics and its application

OECD FORD branch

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Project

<a href="/en/project/VS96122" target="_blank" >VS96122: Resarch Laboratory for Mechatronic Systems</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

1999

Confidentiality

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

Name of the periodical

Zeszyty naukowe katedry mechaniki stosowanej

ISSN

83-911764-0-1

e-ISSN

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Volume of the periodical

1999

Issue of the periodical within the volume

11

Country of publishing house

US - UNITED STATES

Number of pages

4

Pages from-to

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UT code for WoS article

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EID of the result in the Scopus database

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