id |
ndltd-OhioLink-oai-etd.ohiolink.edu-ucin1154637611
|
record_format |
oai_dc
|
spelling |
ndltd-OhioLink-oai-etd.ohiolink.edu-ucin11546376112021-08-03T06:11:26Z Modeling of BJT in VHDL-AMS Madala, Raghu Sagar In this thesis we describe several bipolar junction transistor (BJT) models written in VHDL-AMS that are accurate, robust and provide good performance. With the increasing applications of mixed-signal systems, the ability to identify the capabilities of mixed-signal languages is needed to model these systems efficiently. The ability of VHDL-AMS to represent ordinary differential equations and process discontinuities is of high importance when modeling mixed-signal systems. In this research static and large-signal Ebers Moll and Gummel Poon models have been developed in VHDL-AMS. The Gummel Poon model described in this thesis is complex, and provides the basis for all the subsequent BJT models. These models are compared against SPICE for accuracy and performance. 2006-10-02 English text University of Cincinnati / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ucin1154637611 http://rave.ohiolink.edu/etdc/view?acc_num=ucin1154637611 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
|
collection |
NDLTD
|
language |
English
|
sources |
NDLTD
|
author |
Madala, Raghu Sagar
|
spellingShingle |
Madala, Raghu Sagar
Modeling of BJT in VHDL-AMS
|
author_facet |
Madala, Raghu Sagar
|
author_sort |
Madala, Raghu Sagar
|
title |
Modeling of BJT in VHDL-AMS
|
title_short |
Modeling of BJT in VHDL-AMS
|
title_full |
Modeling of BJT in VHDL-AMS
|
title_fullStr |
Modeling of BJT in VHDL-AMS
|
title_full_unstemmed |
Modeling of BJT in VHDL-AMS
|
title_sort |
modeling of bjt in vhdl-ams
|
publisher |
University of Cincinnati / OhioLINK
|
publishDate |
2006
|
url |
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1154637611
|
work_keys_str_mv |
AT madalaraghusagar modelingofbjtinvhdlams
|
_version_ |
1719432415734136832
|