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Noncausal image modeling using descriptor approach

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dc.contributor.authorAzimi-Sadjadi, Mahmood R., author
dc.contributor.authorHasan, Mohammed A., author
dc.contributor.authorIEEE, publisher
dc.date.accessioned2007-01-03T04:18:38Z
dc.date.available2007-01-03T04:18:38Z
dc.date.issued1995
dc.descriptionNot digitized by CSUL Digital Services.
dc.description.abstractThe problems of noncausal image modeling and subsequent image estimation are considered in this brief. The noncausal vector autoregressive (AR) model for the image process is arranged into a descriptor system. This system is then decomposed into backward and forward stable subsystems. The resulting subsystems are utilized to derive a Kalman filter by solving some types of discrete time algebraic Lyapunov equations. A numerical example for noncausal image modeling is also presented.
dc.format.mediumarticles
dc.identifier.bibliographicCitationHasan, Mohammed A. and Mahmood R. Azimi-Sadjadi, Noncausal Image Modeling Using Descriptor Approach, IEEE Transactions on Circuits and Systems. II, Analog and Digital Signal Processing 42, no. 8 (August 1995): 536-540.
dc.identifier.urihttp://hdl.handle.net/10217/990
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©1995 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.subjectautoregressive processes
dc.subjectLyapunov matrix equations
dc.subjectKalman filters
dc.subjectfiltering theory
dc.subjectimage processing
dc.titleNoncausal image modeling using descriptor approach
dc.typeText

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