2017
DOI: 10.1002/cta.2386
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Competitive evolutionary algorithms for building performance database of a microwave transistor

Abstract: In this work, the simultaneous trade-off relations among the noise figure F, gain G T , input V in , and output V out VSWRs of a microwave transistor operated at a certain (V DS , I DS , f) condition are obtained fast and as accurate as the corresponding analytical results using multiobjective optimization process without any need for expertise on the microwave device, circuit, and noise. Three powerful evolutionary algorithms, cuckoo search, firefly, and differential evolution, are implemented comparatively a… Show more

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Cited by 22 publications
(23 citation statements)
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“…Design optimization of the CFA has been achieved by using the proposed M2LP model and a meta-heuristic optimization algorithm differential evolutionary algorithm (DEA). 48 In this optimization problem, S 11 (outputs of M2LP) of the design Table 1) using the cost function given in Equation (5)…”
Section: Resultsmentioning
confidence: 99%
“…Design optimization of the CFA has been achieved by using the proposed M2LP model and a meta-heuristic optimization algorithm differential evolutionary algorithm (DEA). 48 In this optimization problem, S 11 (outputs of M2LP) of the design Table 1) using the cost function given in Equation (5)…”
Section: Resultsmentioning
confidence: 99%
“…In conjunction with selection, the perturbation effect self‐organizes the sampling of the problem space, bounding it to known areas of interest . Recently, there had been many studies on optimization of microwave devices via the use of DEA algorithm …”
Section: Design Optimization Of the Mlp Based Antenna Model Via The Umentioning
confidence: 99%
“…[53][54][55][56][57] Recently, there had been many studies on optimization of microwave devices via the use of DEA algorithm. [58][59][60][61][62][63] In this section, the design optimization of the proposed varicap diode loaded microstrip patch antenna is achieved by using both MLP based model and the DEA algorithm, where the cost function for optimization process based on the antennas return loss characteristics obtained via the use of MLP based model. In this optimization problem the return loss characteristic of the design would change with respect to the antenna's design parameters which are also the input variables of the MLP model.…”
Section: Design Optimization Of the Mlp Based Antenna Model Via Thementioning
confidence: 99%
“…The proposed PLTWA and its optimally selected design parameters of are given respectively, in Figure and Table . The values given in Table are obtained via a design optimization process by using differential evolutionary optimization algorithm . In Equation , the cost function for design optimization of PLTWA is given. Cost0.25em(),,LiWjfr=min{}S11+max{}Gain …”
Section: Design and Simulationmentioning
confidence: 99%