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Estimation and identification for 2-D block Kalman filtering

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dc.contributor.authorAzimi-Sadjadi, Mahmood R., author
dc.contributor.authorIEEE, publisher
dc.date.accessioned2007-01-03T04:49:11Z
dc.date.available2007-01-03T04:49:11Z
dc.date.issued1991
dc.description.abstractThis correspondence is concerned with the development of a recursive identification and estimation procedure for 2-D block Kalman filtering. The recursive identification scheme can be used on-line to update the image model parameters at each iteration based upon the local statistics within a block of the observed noisy image. The covariance matrix of the driving noise can also be estimated at each iteration of this algorithm. A recursive procedure is given for computing the parameters of the higher order models. Simulation results are also provided.
dc.format.mediumborn digital
dc.format.mediumarticles
dc.identifier.bibliographicCitationAzimi-Sadjadi, Mahmood R., Estimation and Identification for 2-D Block Kalman Filtering, IEEE Transactions on Signal Processing 39, no. 8 (August 1991): 1885-1889.
dc.identifier.urihttp://hdl.handle.net/10217/933
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©1991 IEEE.
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectKalman filters
dc.subjectadaptive filters
dc.subjectpicture processing
dc.subjectidentification
dc.subjectfiltering and prediction theory
dc.subjectparameter estimation
dc.titleEstimation and identification for 2-D block Kalman filtering
dc.typeText

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