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  • The paper deals with methods for estimation of spectral characteristics of signals generated by cardiovascular system. Considering character of CVS signals, parametric algorithms based on AR models seem to have convenient properties for this purpose. Because classical methods used for estimation of AR parameters are not robust and accurate enough genetic algorithm was used for parameter estimation.
  • The paper deals with methods for estimation of spectral characteristics of signals generated by cardiovascular system. Considering character of CVS signals, parametric algorithms based on AR models seem to have convenient properties for this purpose. Because classical methods used for estimation of AR parameters are not robust and accurate enough genetic algorithm was used for parameter estimation. (en)
Title
  • Genetic Algorithms in Spectral Analysis of CVS Signals
  • Genetic Algorithms in Spectral Analysis of CVS Signals (en)
skos:prefLabel
  • Genetic Algorithms in Spectral Analysis of CVS Signals
  • Genetic Algorithms in Spectral Analysis of CVS Signals (en)
skos:notation
  • RIV/00216305:26220/99:4360024!RIV/2000/MSM/262200
http://linked.open.../vavai/riv/strany
  • 55
http://linked.open...avai/riv/aktivita
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  • Z(MSM 262200011)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
  • Holčík, Jiří
  • Hédl, Radek
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  • 741237
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  • RIV/00216305:26220/99:4360024
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  • frequency spectrum; genetic algorithm; cardiovascular system (en)
http://linked.open.../riv/klicoveSlovo
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  • [EB358A4C50AC]
http://linked.open...i/riv/mistoVydani
  • Plzeň
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  • Applied Electronics \\\'99
http://linked.open...in/vavai/riv/obor
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  • Holčík, Jiří
  • Hédl, Radek
http://linked.open...n/vavai/riv/zamer
number of pages
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  • Západočeská universita, Plzeň
https://schema.org/isbn
  • 80-7082-512-X
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  • 26220
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