Estimation of AR Model Parameters of the CVS Signals Using Genetic Algorithms

Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F00%3A4360006" target="_blank" >RIV/00216305:26220/00:4360006 - isvavai.cz</a>
Výsledek na webu
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Jazyk výsledku
angličtina
Název v původním jazyce
Estimation of AR Model Parameters of the CVS Signals Using Genetic Algorithms
Popis výsledku v původním jazyce
The paper deals with methods for estimation of spectral characteristics of signals generated by cardiovascular system (CVS). Considering the character of CVS signals, parametric algorithms based on autoregressive (AR) models seem to have convenient p roperties for this purpose. Bacause classical methods used for estimation of AR model parameters are not robust and accurate enough it is necessary to find some more reliable ones. Genetic algorithms took to be a proper tool that can help us. Applyin g of the genetic algorithms for estimation of AR model parameters is the main aim of this work.
Název v anglickém jazyce
Estimation of AR Model Parameters of the CVS Signals Using Genetic Algorithms
Popis výsledku anglicky
The paper deals with methods for estimation of spectral characteristics of signals generated by cardiovascular system (CVS). Considering the character of CVS signals, parametric algorithms based on autoregressive (AR) models seem to have convenient p roperties for this purpose. Bacause classical methods used for estimation of AR model parameters are not robust and accurate enough it is necessary to find some more reliable ones. Genetic algorithms took to be a proper tool that can help us. Applyin g of the genetic algorithms for estimation of AR model parameters is the main aim of this work.

Rok uplatnění
2000
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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