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...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2008
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| Subjects: | |
| Online Access: | http://scholars.utp.edu.my/id/eprint/2782/ http://scholars.utp.edu.my/id/eprint/2782/1/WCE08.PDF |
| Summary: | 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. |
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