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.
Saved in:
Main Authors: | Banookh,Amir, Barakati,S. Masoud |
---|---|
Format: | Digital revista |
Language: | English |
Published: |
Sociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de Eletromagnetismo
2012
|
Online Access: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742012000100017 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Bird Swarm Algorithm and Particle Swarm Optimization in Ensemble Recurrent Neural Networks Optimization for Time Series Prediction
by: Pulido,Martha, et al.
Published: (2024) -
Microcalcification Detection in Mammograms Using Particle Swarm Optimization and Probabilistic Neural Network
by: Touami,Rachida, et al.
Published: (2021) -
Time-series forecasting of pollutant concentration levels using particle swarm optimization and artificial neural networks
by: Albuquerque Filho,Francisco S. de, et al.
Published: (2013) -
Particle swarm optimization in WDM/OCDM networks with physical impairments
by: Durand,Fábio R., et al.
Published: (2013) -
Adaptive underfrequency load shedding using particle swarm optimization algorithm
by: Ketabi,Abbas, et al.
Published: (2017)