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Description
  • An extension of the AutoRegressive (AR) model is studied, which allows transformations and distortions on the regressor to be handled. It is shown that Bayesian identification and prediction of EAR model does, however, require that the transformation be known. When it is unknown, the associated transformation space is represented by a finite set of candidates. An approximate identification algorithm for MEAR is developed, and applied to identification of signal in burst noise and speech reconstruction.
  • An extension of the AutoRegressive (AR) model is studied, which allows transformations and distortions on the regressor to be handled. It is shown that Bayesian identification and prediction of EAR model does, however, require that the transformation be known. When it is unknown, the associated transformation space is represented by a finite set of candidates. An approximate identification algorithm for MEAR is developed, and applied to identification of signal in burst noise and speech reconstruction. (en)
  • Základní autoregresní (AR) model je rozšířen o možnost transformace regresoru, která umožní modelování různých zkreslení AR modelu. Pokud je tato transformační funkce známa je odhad rozšířeného modelu stejný jako odhad AR modelu. V tomto příspěvku se zabýváme reprezentací neznámé transformační funkce pomocí konečné množiny konkrétních funkcí. Je zde prezentován aproximativní algoritmus odhadu takovéhoto směsového modelu a jeho aplikace pro rekonstrukci zašuměného signálu. (cs)
Title
  • Mixture-based extension of the AR model and its recursive Bayesian identification
  • Směsové rozšíření AR modelu a jeho rekurzivní Bayesovské odhadování (cs)
  • Mixture-based extension of the AR model and its recursive Bayesian identification (en)
skos:prefLabel
  • Mixture-based extension of the AR model and its recursive Bayesian identification
  • Směsové rozšíření AR modelu a jeho rekurzivní Bayesovské odhadování (cs)
  • Mixture-based extension of the AR model and its recursive Bayesian identification (en)
skos:notation
  • RIV/67985556:_____/05:00411452!RIV06-AV0-67985556
http://linked.open.../vavai/riv/strany
  • 3530;3542
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1M0572), P(GA102/03/0049), P(IBS1075102), Z(AV0Z10750506)
http://linked.open...iv/cisloPeriodika
  • 9
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 530412
http://linked.open...ai/riv/idVysledku
  • RIV/67985556:_____/05:00411452
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • AR model; Bayesian identification; Variational Bayes (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...odStatuVydavatele
  • US - Spojené státy americké
http://linked.open...ontrolniKodProRIV
  • [FE866F0FDE7B]
http://linked.open...i/riv/nazevZdroje
  • IEEE Transactions on Signal Processing
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...v/svazekPeriodika
  • 53
http://linked.open...iv/tvurceVysledku
  • Šmídl, Václav
  • Quinn, A.
http://linked.open...n/vavai/riv/zamer
issn
  • 1053-587X
number of pages
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