Linear and Non-Linear Models for Signal Prediction

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F09%3A00022098" target="_blank" >RIV/60461373:22340/09:00022098 - 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

Linear and Non-Linear Models for Signal Prediction

Original language description

The focus of the study is in the proposal of a suitable prediction model and comparison of results of different methods. Methods presented include polynomial models, autoregressive models, linear neural networks, adaptive linear element, feed-forward neural networks, the Elman neural networks and a recurrent neural networks with a real time recurrent learning algorithm. The created algorithms have been then applied for processing of real data representing gas consumption in the Czech Republic.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2009

Confidentiality

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

Article name in the collection

Proceedings 17th Annual Conference Technical Computing Prague 2009

ISBN

978-80-7080-733-0

ISSN

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e-ISSN

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Number of pages

20

Pages from-to

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Publisher name

Humusoft

Place of publication

Praha

Event location

Praha

Event date

Nov 19, 2009

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

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