Optimal design of double folded stub microstrip filter by neural network modelling and particle swarm optimization
Optimization of design parameters based on electromagnetic simulation of microwave circuits is a timeconsuming and iterative procedure. To provide a fast and accurate frequency response for a given case study, this paper employs a neural network modelling approach. First, one of the case study's outputs, i.e., scattering parameter (|S21|) in dB, is predicted using a neural network model. Then the particle swarm optimization is employed to optimize the design parameters. The proposed method in designing the filter compares with two others methods for a case study. The simulation results show the capability of the proposed method in designing an optimized filter in a proper time.
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Sociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de Eletromagnetismo
2012
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oai:scielo:S2179-107420120001000172012-07-16Optimal design of double folded stub microstrip filter by neural network modelling and particle swarm optimizationBanookh,AmirBarakati,S. Masoud neural networks Microwave structures particle swarm optimization modelling Optimization of design parameters based on electromagnetic simulation of microwave circuits is a timeconsuming and iterative procedure. To provide a fast and accurate frequency response for a given case study, this paper employs a neural network modelling approach. First, one of the case study's outputs, i.e., scattering parameter (|S21|) in dB, is predicted using a neural network model. Then the particle swarm optimization is employed to optimize the design parameters. The proposed method in designing the filter compares with two others methods for a case study. The simulation results show the capability of the proposed method in designing an optimized filter in a proper time.info:eu-repo/semantics/openAccessSociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de EletromagnetismoJournal of Microwaves, Optoelectronics and Electromagnetic Applications v.11 n.1 20122012-06-01info:eu-repo/semantics/articletext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742012000100017en10.1590/S2179-10742012000100017 |
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Banookh,Amir Barakati,S. Masoud |
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Banookh,Amir Barakati,S. Masoud Optimal design of double folded stub microstrip filter by neural network modelling and particle swarm optimization |
| author_facet |
Banookh,Amir Barakati,S. Masoud |
| author_sort |
Banookh,Amir |
| title |
Optimal design of double folded stub microstrip filter by neural network modelling and particle swarm optimization |
| title_short |
Optimal design of double folded stub microstrip filter by neural network modelling and particle swarm optimization |
| title_full |
Optimal design of double folded stub microstrip filter by neural network modelling and particle swarm optimization |
| title_fullStr |
Optimal design of double folded stub microstrip filter by neural network modelling and particle swarm optimization |
| title_full_unstemmed |
Optimal design of double folded stub microstrip filter by neural network modelling and particle swarm optimization |
| title_sort |
optimal design of double folded stub microstrip filter by neural network modelling and particle swarm optimization |
| description |
Optimization of design parameters based on electromagnetic simulation of microwave circuits is a timeconsuming and iterative procedure. To provide a fast and accurate frequency response for a given case study, this paper employs a neural network modelling approach. First, one of the case study's outputs, i.e., scattering parameter (|S21|) in dB, is predicted using a neural network model. Then the particle swarm optimization is employed to optimize the design parameters. The proposed method in designing the filter compares with two others methods for a case study. The simulation results show the capability of the proposed method in designing an optimized filter in a proper time. |
| publisher |
Sociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de Eletromagnetismo |
| publishDate |
2012 |
| url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742012000100017 |
| work_keys_str_mv |
AT banookhamir optimaldesignofdoublefoldedstubmicrostripfilterbyneuralnetworkmodellingandparticleswarmoptimization AT barakatismasoud optimaldesignofdoublefoldedstubmicrostripfilterbyneuralnetworkmodellingandparticleswarmoptimization |
| _version_ |
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