Automated Macromodel Generation for High Level Modeling
In this paper we present a novel approach termed multiple model generation system (MMGS) for extracting either single-input single-output (SISO) or multiple-input single-output (MISO) macromodels from a SPICE netlist. It detects nonlinearity through variations in output error. The multiple model con...
| 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/2785/ http://scholars.utp.edu.my/id/eprint/2785/1/DTIS08-69.pdf |
| Summary: | In this paper we present a novel approach termed multiple model generation system (MMGS) for extracting either single-input single-output (SISO) or multiple-input single-output (MISO) macromodels from a SPICE netlist. It detects nonlinearity through variations in output error. The multiple model conversion system (MMCS) is developed to automatically convert these models from MMGS into hardware description language (HDL) models for either SISO or MISO macromodels and behave as the operational amplifier (op amp). We demonstrate the application of MMGS using a two-stage CMOS operational amplifier (op amp), comparing simulations of the macromodel against those of the original SPICE circuit utilizing transient analysis. |
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