This work for the first time shows that physically meaningful, wideband, multi-bias small-signal modeling of HBTs can be efficiently and accurately achieved using a genetic Algorithm (GA). The physical significance of the equivalent circuit parameters extracted by the GA was checked using a Direct Extraction Technique (DET). The two procedures were applied to HBT S-parameters measured at different bias points. The simulated S-parameters match very well with the measured ones over the whole frequency range investigated. For each point we obtained quite a good agreement between the parameters extracted by the DET and by the GA, which demonstartes the ability of the GA to efficiently extract a physically significant HBT small-signal model.

A comparison between HBt small-signal model optimization using a genetic algorithm and direct parametric extraction / Borgarino, Mattia; R., Menozzi; J., Tasselli; A., Marty. - STAMPA. - Not available:(1998), pp. 291-296. (Intervento presentato al convegno Gallium Arsenide and related III-V Compounds Application Symposium tenutosi a Amsterdam (The Netherlands) nel 5-6, october 1998).

A comparison between HBt small-signal model optimization using a genetic algorithm and direct parametric extraction

BORGARINO, Mattia;
1998

Abstract

This work for the first time shows that physically meaningful, wideband, multi-bias small-signal modeling of HBTs can be efficiently and accurately achieved using a genetic Algorithm (GA). The physical significance of the equivalent circuit parameters extracted by the GA was checked using a Direct Extraction Technique (DET). The two procedures were applied to HBT S-parameters measured at different bias points. The simulated S-parameters match very well with the measured ones over the whole frequency range investigated. For each point we obtained quite a good agreement between the parameters extracted by the DET and by the GA, which demonstartes the ability of the GA to efficiently extract a physically significant HBT small-signal model.
1998
Gallium Arsenide and related III-V Compounds Application Symposium
Amsterdam (The Netherlands)
5-6, october 1998
Not available
291
296
Borgarino, Mattia; R., Menozzi; J., Tasselli; A., Marty
A comparison between HBt small-signal model optimization using a genetic algorithm and direct parametric extraction / Borgarino, Mattia; R., Menozzi; J., Tasselli; A., Marty. - STAMPA. - Not available:(1998), pp. 291-296. (Intervento presentato al convegno Gallium Arsenide and related III-V Compounds Application Symposium tenutosi a Amsterdam (The Netherlands) nel 5-6, october 1998).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/594872
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