Optimization of Filter by using Support Vector Regression Machine with Cuckoo Search Algorithm
Loading...
Date
2014-09
ORCID
Advisor
Referee
Mark
Journal Title
Journal ISSN
Volume Title
Publisher
Společnost pro radioelektronické inženýrství
Abstract
Herein, a new methodology using a 3D Electromagnetic (EM) simulator-based Support Vector Regression Machine (SVRM) models of base elements is presented for band-pass filter (BPF) design. SVRM models of elements, which are as fast as analytical equations and as accurate as a 3D EM simulator, are employed in a simple and efficient Cuckoo Search Algorithm (CSA) to optimize an ultra-wideband (UWB) microstrip BPF. CSA performance is verified by comparing it with other Meta-Heuristics such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). As an example of the proposed design methodology, an UWB BPF that operates between the frequencies of 3.1 GHz and 10.6 GHz is designed, fabricated and measured. The simulation and measurement results indicate in conclusion the superior performance of this optimization methodology in terms of improved filter response characteristics like return loss, insertion loss, harmonic suppression and group delay.
Description
Citation
Radioengineering. 2014, vol. 23, č. 3, s. 790-797. ISSN 1210-2512
http://www.radioeng.cz/fulltexts/2014/14_03_0790_0797.pdf
http://www.radioeng.cz/fulltexts/2014/14_03_0790_0797.pdf
Document type
Peer-reviewed
Document version
Published version
Date of access to the full text
Language of document
en