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Design, high-level synthesis, and discrete optimization of digital filters based on particle swarm optimization Open Access


Other title
Particle swarm optimization
Digital filters
High-level synthesis
Type of item
Degree grantor
University of Alberta
Author or creator
Hashemi, Seyyed Ali
Supervisor and department
Nowrouzian, Behrouz (Electrical and Computer Engineering)
Examining committee member and department
Dinavahi, Venkata (Electrical and Computer Engineering)
Moez, Kambiz (Electrical and Computer Engineering)
Han, Bin (Mathematical and Statistical Sciences)
Department of Electrical and Computer Engineering

Date accepted
Graduation date
Master of Science
Degree level
This thesis is concerned with the development of a novel discrete particle swarm optimization (PSO) technique and its application to the discrete optimization of digital filter frequency response characteristics on the one hand, and the high-level synthesis of bit-parallel digital filter data-paths on the other. Two different techniques are presented for the optimization of sharp-transition band frequency response masking (FRM) digital filters, one of which is based on the conventional finite impulse-response (FIR) digital subfilters, and a new hardware-efficient approach which is based on utilizing infinite impulse-response (IIR) digital subfilters. It is shown that further hardware efficiency can be achieved by realizing the IIR interpolation subfilters by using the bilinear-LDI approach. The corresponding discrete PSO is carried out over the canonical signed digit (CSD) multiplier coefficient space for direct mapping to digital hardware considering simultaneous magnitude and group-delay frequency response characteristics. A powerful encoding scheme is developed for the high-level synthesis of digital filters based on discrete PSO, which preserves the data dependency relationships in the digital filter data-paths. In addition, a constrained discrete PSO is developed to overcome the limitations which would manifest themselves if the conventional PSO were to be used. Several examples are presented to demonstrate the application of discrete PSO to the design, high-level synthesis and optimization of digital filters.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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