MESFET DC model parameter extraction using Quantum Particle Swarm Optimization

This paper presents two techniques for DC model parameter extraction for a Gallium Arsenide (GaAs) based MEtal Semiconductor Field Effect Transistor (MESFET) device. The proposed methods uses Particle Swarm Optimization (PSO) and Quantum Particle Swarm Optimization (QPSO) methods for optimizing the difference between measured data and simulated data. Simulated data are obtained by using four different popular DC models. These techniques avoid complex computational steps involved in traditional parameter extraction techniques. The performance comparison in terms of quality of solution and execution time of classical PSO and QPSO to extract the model parameters are presented. The validity of this approach is verified by comparing the simulated and measured results of a fabricated GaAs MESFET device with gate length of 0.7 lm and gate width of 600 l m( 4� 150). Simulation results indicate that both the technique based on PSO and QPSO accurately extracts the model parameters of MESFET.

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