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Identification and approximation of one-dimensional and two-dimensional digital filters

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Date Issued:
1998
Summary:
In this dissertation, identification and approximation of one-dimensional (1-D) and two-dimensional (2-D) recursive digital filters are addressed. In the identification phase, a novel Neural Network (NN) structure is proposed which provides the state-space model of 1-D filters based upon input-output data. The state space identification technique is also extended to 2-D digital filters and several comparison studies are performed. In the approximation phase, frequency-domain balanced structures for 1-D as well as 2-D digital filters are proposed. The model reduction technique is based on the conceptual view point of balancing the controllability and observability Grammians of a digital filter in an arbitrary frequency range of operation. Finally, the interrelations between these two phases are presented. Extensive simulation experiments are presented to demonstrate the effectiveness of proposed methods.
Title: Identification and approximation of one-dimensional and two-dimensional digital filters.
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Name(s): Wang, Dali.
Florida Atlantic University, Degree grantor
Zilouchian, Ali, Thesis advisor
College of Engineering and Computer Science
Department of Computer and Electrical Engineering and Computer Science
Type of Resource: text
Genre: Electronic Thesis Or Dissertation
Issuance: monographic
Date Issued: 1998
Publisher: Florida Atlantic University
Place of Publication: Boca Raton, Fla.
Physical Form: application/pdf
Extent: 197 p.
Language(s): English
Summary: In this dissertation, identification and approximation of one-dimensional (1-D) and two-dimensional (2-D) recursive digital filters are addressed. In the identification phase, a novel Neural Network (NN) structure is proposed which provides the state-space model of 1-D filters based upon input-output data. The state space identification technique is also extended to 2-D digital filters and several comparison studies are performed. In the approximation phase, frequency-domain balanced structures for 1-D as well as 2-D digital filters are proposed. The model reduction technique is based on the conceptual view point of balancing the controllability and observability Grammians of a digital filter in an arbitrary frequency range of operation. Finally, the interrelations between these two phases are presented. Extensive simulation experiments are presented to demonstrate the effectiveness of proposed methods.
Identifier: 9780591776874 (isbn), 12555 (digitool), FADT12555 (IID), fau:9443 (fedora)
Collection: FAU Electronic Theses and Dissertations Collection
Note(s): College of Engineering and Computer Science
Thesis (Ph.D.)--Florida Atlantic University, 1998.
Subject(s): Digital filters (Mathematics)
Signal processing--Digital technique
Electric filters, Digital
Held by: Florida Atlantic University Libraries
Persistent Link to This Record: http://purl.flvc.org/fcla/dt/12555
Sublocation: Digital Library
Use and Reproduction: Copyright © is held by the author, with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
Use and Reproduction: http://rightsstatements.org/vocab/InC/1.0/
Host Institution: FAU
Is Part of Series: Florida Atlantic University Digital Library Collections.