This paper tackles the analog and mixed-signal modeling for verification challenges. It proposes an adjustable automated modeling approach, which provides set-valued models with reduced overapproximation. The models reliably enclose parameter variations and modeling errors. The reduced overapproximation is obtained by computing the intersecting set of models with intervals and affine forms. The nonlinear circuit examples show a reduced overapproximation up to 86%.

中文翻译：

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将非线性模拟电路自动抽象为可靠的设定值模型，从而减少了过逼近

本文针对验证挑战解决了模拟和混合信号建模问题。它提出了一种可调整的自动建模方法，该方法可提供具有减少的过逼近的集值模型。这些模型可靠地包含了参数变化和建模误差。通过计算具有间隔和仿射形式的交叉模型集，可以得到减少的过逼近。非线性电路示例显示出减少的过逼近率高达86％。