Optimal design of double folded stub microstrip filter by neural network modelling and particle swarm optimization

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Abstract

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 (|S 21|) 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. © 2012 SBMO/SBMag.

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APA

Banookh, A., & Barakati, S. M. (2012). Optimal design of double folded stub microstrip filter by neural network modelling and particle swarm optimization. Journal of Microwaves, Optoelectronics and Electromagnetic Applications, 11(1), 204–213. https://doi.org/10.1590/S2179-10742012000100017

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