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Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Engineering

TÜBİTAK

Journal

2012

FET modeling

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

A Modified Particle Swarm Optimization Algorithm And Its Application To The Multiobjective Fet Modeling Problem, Ufuk Özkaya, Fi̇li̇z Güneş Jan 2012

A Modified Particle Swarm Optimization Algorithm And Its Application To The Multiobjective Fet Modeling Problem, Ufuk Özkaya, Fi̇li̇z Güneş

Turkish Journal of Electrical Engineering and Computer Sciences

This paper introduces a modified particle swarm algorithm to handle multiobjective optimization problems. In multiobjective PSO algorithms, the determination of Pareto optimal solutions depends directly on the strategy of assigning a best local guide to each particle. In this work, the PSO algorithm is modified to assign a best local guide to each particle by using minimum angular distance information. This algorithm is implemented to determine field-effect transistor (FET) model elements subject to the Pareto domination between the scattering parameters and operation bandwidth. Furthermore, the results are compared with those obtained by the nondominated sorting genetic algorithm-II. FET models are …


Multiobjective Fet Modeling Using Particle Swarm Optimization Based On Scattering Parameters With Pareto Optimal Analysis, Fi̇li̇z Güneş, Ufuk Özkaya Jan 2012

Multiobjective Fet Modeling Using Particle Swarm Optimization Based On Scattering Parameters With Pareto Optimal Analysis, Fi̇li̇z Güneş, Ufuk Özkaya

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, design-oriented field effect transistor (FET) models are produced. For this purpose, FET modeling is put forward as a constrained, multiobjective optimization problem. Two novel methods for multiobjective optimization are employed: particle swarm optimization (PSO) uses the single-objective function, which gathers all of the objectives as aggregating functions; and the nondominated sorting genetic algorithm-II (NSGA-II) sorts all of the trade-off solutions on the Pareto frontiers. The PSO solution is compared with the Pareto optimum solutions in the biobjective plane and the success of the first method is verified. Furthermore, the resulting FET models are compared with similar FET …