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

Result code in 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>

Result on the web

—

DOI - Digital Object Identifier

—

Result language

angličtina

Original language name

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

Original language description

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.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

BC - Theory and management systems

OECD FORD branch

—

Project

—

Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2000

Confidentiality

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

Article name in the collection

MENDEL 2000

ISBN

80-214-1609-2

ISSN

—

e-ISSN

—

Number of pages

5

Pages from-to

—

Publisher name

FSI VUT v Brně

Place of publication

Brno

Event location

—

Event date

—

Type of event by nationality

—

UT code for WoS article

—