Compiled code simulation of analog and mixed-signal systems using piecewise linear modeling of nonlinear parameters: A case study for Δ Σ modulator simulation

Hui Zhang, Simona Doboli, Hua Tang, Alex Doboli

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

This paper presents a methodology for fast time-domain simulation of analog systems with nonlinear parameters. Specifically, the paper focuses on Δ Σ analog-to-digital converters (ADC). The method creates compiled-code simulators based on symbolic analysis. Code is optimized using loop invariant elimination and constant folding, well-known compiler optimization methods. Circuits are described as structural macromodels. Nonlinear parameters are expressed using piecewise linear (PWL) models. The paper presents a technique for automatically creating PWL models through model extraction from trained neural networks. As compared to existing behavioral simulation methods for Δ Σ ADC, this technique is more systematic and accurate. In our experiments, compiled-code simulation was significantly faster than numerical simulation. Hence, the methodology is very useful in analog and mixed-signal system synthesis, which is known to require a large number of simulation steps.

Original languageEnglish (US)
Pages (from-to)193-208
Number of pages16
JournalIntegration, the VLSI Journal
Volume40
Issue number3
DOIs
StatePublished - Apr 2007

Keywords

  • Analog and mixed-signal systems
  • Neural networks
  • Nonlinear modeling
  • Piecewise linear
  • Simulation

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