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An Automated Model Generation Approach for High Level Modelling

Over the last few years automated model generation has become an increasingly important component of methodologies for verification of large, complex mix-signal SoCs (system-on-chips) and SiPs (system-in-packages). In this paper a novel approach termed Multiple Model Generation System using Delta op...

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Main Authors: Xia, Likun, Bell, Ian, Wilkinson, Antony
Format: Conference or Workshop Item
Published: 2008
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utp.edu.my/2782/1/WCE08.PDF
http://www.iaeng.org/publication/WCE2008/
http://eprints.utp.edu.my/2782/
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spelling my.utp.eprints.27822017-01-19T08:26:13Z An Automated Model Generation Approach for High Level Modelling Xia, Likun Bell, Ian Wilkinson, Antony TK Electrical engineering. Electronics Nuclear engineering Over the last few years automated model generation has become an increasingly important component of methodologies for verification of large, complex mix-signal SoCs (system-on-chips) and SiPs (system-in-packages). In this paper a novel approach termed Multiple Model Generation System using Delta operator (MMGSD) is developed for extracting either single-input single-output (SISO) or multiple-input single-output (MISO) macromodels from a SPICE netlist. This model generation process detects nonlinearity through variations in output error. Examples of the application of MMGSD are presented for simple two-input systems incorporating a two-stage CMOS operational amplifier (op amp). We demonstrate the generated models are able to model various circuits with good accuracy. 2008-07 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/2782/1/WCE08.PDF http://www.iaeng.org/publication/WCE2008/ Xia, Likun and Bell, Ian and Wilkinson, Antony (2008) An Automated Model Generation Approach for High Level Modelling. In: World Congress on Engineering (WCE) 2008, July2-4, 2008, London, UK. http://eprints.utp.edu.my/2782/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Xia, Likun
Bell, Ian
Wilkinson, Antony
An Automated Model Generation Approach for High Level Modelling
description Over the last few years automated model generation has become an increasingly important component of methodologies for verification of large, complex mix-signal SoCs (system-on-chips) and SiPs (system-in-packages). In this paper a novel approach termed Multiple Model Generation System using Delta operator (MMGSD) is developed for extracting either single-input single-output (SISO) or multiple-input single-output (MISO) macromodels from a SPICE netlist. This model generation process detects nonlinearity through variations in output error. Examples of the application of MMGSD are presented for simple two-input systems incorporating a two-stage CMOS operational amplifier (op amp). We demonstrate the generated models are able to model various circuits with good accuracy.
format Conference or Workshop Item
author Xia, Likun
Bell, Ian
Wilkinson, Antony
author_facet Xia, Likun
Bell, Ian
Wilkinson, Antony
author_sort Xia, Likun
title An Automated Model Generation Approach for High Level Modelling
title_short An Automated Model Generation Approach for High Level Modelling
title_full An Automated Model Generation Approach for High Level Modelling
title_fullStr An Automated Model Generation Approach for High Level Modelling
title_full_unstemmed An Automated Model Generation Approach for High Level Modelling
title_sort automated model generation approach for high level modelling
publishDate 2008
url http://eprints.utp.edu.my/2782/1/WCE08.PDF
http://www.iaeng.org/publication/WCE2008/
http://eprints.utp.edu.my/2782/
_version_ 1738655221318418432
score 13.211869

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