Title
Genetic algorithms for designing digital filters
Date of Award
2008
Publication Type
Master Thesis
Degree Name
M.A.Sc.
Department
Electrical and Computer Engineering
First Advisor
Kobti, Ziad (School of Computer Science), Kar, Narayan (Electrical & Computer Engineering)
Keywords
Engineering, Electronics and Electrical.
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Abstract
This thesis presents a method of adapting IIR filters implemented as lattice structures using a Genetic Algorithm (GA), called ZGA. This method addresses some of the difficulties encountered with existing methods of adaptation, providing guaranteed filter stability and the ability to search multi-modal error surfaces. ZGA mainly focuses on convergence improvement in respects of crossover and mutation operators. Four kinds of crossover methods are used to scan as much as possible the potential solution area, only the best of them will be taken as ZGA crossover offspring. And ZGA mutation takes the best of three mutation results as final mutation offspring. Simulation results are presented, demonstrating the suitability of ZGA to the problem of IIR system identification and comparing with the results of Standard GA, Genitor and NGA.
Recommended Citation
Zhang, Hongmei, "Genetic algorithms for designing digital filters" (2008). Electronic Theses and Dissertations. 2208.
https://scholar.uwindsor.ca/etd/2208