2006 13th IEEE International Conference on Electronics, Circuits and Systems 2006
DOI: 10.1109/icecs.2006.379784
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Biobjective Hybrid Evolutionary Algorithm Applied to Resonator Filters of Arbitrary Topology

Abstract: This paper presents a hybrid evolutionary algorithm to synthesize the resonator filters of an arbitrary topology. In this approach the structure space is explored concerning predefined small building-blocks having specific functionalities (resonator or coupling) and rules for structural restrictions. The method used 2D representation, proposing new strong genetic operators and combining a biobejctive evolutionary algorithm to evolve topologies and local search to improve the circuit parameters. The results sho… Show more

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Cited by 2 publications
(2 citation statements)
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“…However, it is a difficult problem, requiring a balance between optimizing topologies and parameters and also presents several open issues. The hybrid evolutionary method presented in this chapter has evolved over time (Dantas, 2006a(Dantas, , 2006b(Dantas, , 2007. The latest proposal, with representation for circuit elements of two ports, using the Positional Matrix, is appropriate to obtain arbitrary topologies and parameters of circuits using small populations, few generations and with a low computational cost.…”
Section: Discussionmentioning
confidence: 99%
“…However, it is a difficult problem, requiring a balance between optimizing topologies and parameters and also presents several open issues. The hybrid evolutionary method presented in this chapter has evolved over time (Dantas, 2006a(Dantas, , 2006b(Dantas, , 2007. The latest proposal, with representation for circuit elements of two ports, using the Positional Matrix, is appropriate to obtain arbitrary topologies and parameters of circuits using small populations, few generations and with a low computational cost.…”
Section: Discussionmentioning
confidence: 99%
“…Both analytical and numerical methods for the synthesis of coupling matrices corresponding to cross-coupled filters have been extensively studied. Recently, a class of hybrid optimization methods combining local search methods with global methods had been reported [1][2][3][4]. For example, the paper in [2] presented a method consists of a Levenberg-Marquardt algorithm for a local optimizer and genetic algorithm for a global optimizer, respectively.…”
Section: Introductionmentioning
confidence: 99%