About: Off-line Estimation of System Noise Covariance Matrices by aOff-line Estimation of System Noise Covariance Matrices by a Special Choice of the Filter Gain     Goto   Sponge   NotDistinct   Permalink

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Description
  • Článek se zabývá odhadem kovariančních matic poruch působících v lineárním a nelineárním systému. Navržená technika odhadu kovariačních matic je založena na analýze statistických vlastnstí inovační posloupnosti Kalmanova filtru a filtrů lokálních. Důraz je kladen na ty situace, kdy je známa počáteční podmínka systému. Teoretické výsledky jsou v závěru ilustrovany na dvou ilustračních příkladech. (cs)
  • Estimation of noise covariance matrices for linear or nonlinear stochastic dynamic systems is treated. The stress is laid on the case when the initial state mean and covariance matrix are exactly known. The properties of the innovation sequence of the Kalman Filter and the local filters are discussed and the new off-line method for estimation of the covariance matrices of the state and the measurement noise is designed. The proposed method is based on special choice of the filter gain and it takes an advantage of the well-known standard relations from the area of state estimation techniques and least square method. The theoretical results are verified in numerical examples.
  • Estimation of noise covariance matrices for linear or nonlinear stochastic dynamic systems is treated. The stress is laid on the case when the initial state mean and covariance matrix are exactly known. The properties of the innovation sequence of the Kalman Filter and the local filters are discussed and the new off-line method for estimation of the covariance matrices of the state and the measurement noise is designed. The proposed method is based on special choice of the filter gain and it takes an advantage of the well-known standard relations from the area of state estimation techniques and least square method. The theoretical results are verified in numerical examples. (en)
Title
  • Off-line Estimation of System Noise Covariance Matrices by aOff-line Estimation of System Noise Covariance Matrices by a Special Choice of the Filter Gain
  • Off-line odhad kovariančních matic poruch systému pomocí vhodné volby zisku filtru (cs)
  • Off-line Estimation of System Noise Covariance Matrices by aOff-line Estimation of System Noise Covariance Matrices by a Special Choice of the Filter Gain (en)
skos:prefLabel
  • Off-line Estimation of System Noise Covariance Matrices by aOff-line Estimation of System Noise Covariance Matrices by a Special Choice of the Filter Gain
  • Off-line odhad kovariančních matic poruch systému pomocí vhodné volby zisku filtru (cs)
  • Off-line Estimation of System Noise Covariance Matrices by aOff-line Estimation of System Noise Covariance Matrices by a Special Choice of the Filter Gain (en)
skos:notation
  • RIV/49777513:23520/07:00000272!RIV08-MSM-23520___
http://linked.open.../vavai/riv/strany
  • 1-6
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1M0572)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
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  • 439055
http://linked.open...ai/riv/idVysledku
  • RIV/49777513:23520/07:00000272
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • stochastic systems, state estimation, Kalman filtering, estimation theory, noise covariance matrices estimation (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [FB72F5AA0C6E]
http://linked.open...v/mistoKonaniAkce
  • Alcalá de Henares
http://linked.open...i/riv/mistoVydani
  • New York
http://linked.open...i/riv/nazevZdroje
  • IEEE International Symposium on Intelligent Signal Processing
http://linked.open...in/vavai/riv/obor
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http://linked.open...vavai/riv/projekt
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http://linked.open...iv/tvurceVysledku
  • Šimandl, Miroslav
  • Duník, Jindřich
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • IEEE
https://schema.org/isbn
  • 1-4244-0830-X
http://localhost/t...ganizacniJednotka
  • 23520
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