In this paper we present a new method to efficiently optimize small-signal equivalent circuits for microwave and millimeter-wave FET linear circuit design. The method couples the stochastic search of a Partially Elitistic Genetic Algorithm with a local search procedure. Up to 19 equivalent circuit elements have been included in the small-signal model for completeness and flexibility. Optimization examples are given for an ion-implanted MESFET up to 12 GHz, a pseudomorphic HEMT up to 50 GHz, and for synthetic data. The results show that the proposed algorithm is able to consistently provide an excellent fit between measured and calculated S-parameters without any need of a careful initial guess for the circuit element values. Also, once the device parasitics have been de-embedded, the algorithm is able to extract unique, physically meaningful values for the intrinsic device parameters, and it is numerically shown not to be affected by measurement uncertainties
Small-signal modeling for microwave FET linear circuits based on a genetic algorithm / Menozzi, Roberto; Piazzi, Aurelio; F., Contini. - In: IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I. FUNDAMENTAL THEORY AND APPLICATIONS. - ISSN 1057-7122. - 43:(1996), pp. 839-847. [10.1109/81.538990]
Small-signal modeling for microwave FET linear circuits based on a genetic algorithm
MENOZZI, Roberto;PIAZZI, Aurelio;
1996-01-01
Abstract
In this paper we present a new method to efficiently optimize small-signal equivalent circuits for microwave and millimeter-wave FET linear circuit design. The method couples the stochastic search of a Partially Elitistic Genetic Algorithm with a local search procedure. Up to 19 equivalent circuit elements have been included in the small-signal model for completeness and flexibility. Optimization examples are given for an ion-implanted MESFET up to 12 GHz, a pseudomorphic HEMT up to 50 GHz, and for synthetic data. The results show that the proposed algorithm is able to consistently provide an excellent fit between measured and calculated S-parameters without any need of a careful initial guess for the circuit element values. Also, once the device parasitics have been de-embedded, the algorithm is able to extract unique, physically meaningful values for the intrinsic device parameters, and it is numerically shown not to be affected by measurement uncertaintiesFile | Dimensione | Formato | |
---|---|---|---|
00538990.pdf
non disponibili
Tipologia:
Documento in Post-print
Licenza:
NON PUBBLICO - Accesso privato/ristretto
Dimensione
927.74 kB
Formato
Adobe PDF
|
927.74 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.