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Mixture-based extension of the AR model and its recursive Bayesian identification
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SYSNO ASEP 0411452 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Ostatní články Title Mixture-based extension of the AR model and its recursive Bayesian identification Title Směsové rozšíření AR modelu a jeho rekurzivní Bayesovské odhadování Author(s) Šmídl, Václav (UTIA-B) RID, ORCID
Quinn, A. (IE)Source Title IEEE Transactions on Signal Processing - ISSN 1053-587X
Roč. 53, č. 9 (2005), s. 3530-3542Number of pages 13 s. Language eng - English Country US - United States Keywords AR model ; Bayesian identification ; Variational Bayes Subject RIV BC - Control Systems Theory R&D Projects IBS1075102 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR) GA102/03/0049 GA ČR - Czech Science Foundation (CSF) 1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) CEZ AV0Z10750506 - UTIA-B (2005-2011) Annotation 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. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2006
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