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This work presents a method 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 generates compiled-code simulators based on symbolic analysis. Code is optimized using loop invariant elimination, and constant folding. 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 (NN). As compared to existing behavioral simulation methods for Δ-Σ ADC, this technique is fully automated and more accurate. In our experiments, compiled-code simulation was about 100× faster than Spectre (numerical) simulation.