Borgarino, M. ; Menozzi, R. ; Tasselli, J. ; Marty, A.
(1998)
A comparison between HBT small-signal model optimization using a genetic algorithm and direct parameter extraction.
In: Gallium Arsenide Applications Symposium. GAAS 1998, 5-6 October 1998, Amsterdam, The Netherlands.
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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 demonstrates the ability of the GA to efficiently extract a physically significant HBT small-signal model.
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 demonstrates the ability of the GA to efficiently extract a physically significant HBT small-signal model.
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(Paper)
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DOI
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16 Feb 2006
Last modified
17 Feb 2016 14:34
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Document type
Conference or Workshop Item
(Paper)
Creators
Subjects
DOI
Deposit date
16 Feb 2006
Last modified
17 Feb 2016 14:34
URI
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