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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.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.mediumborn digital
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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