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Automated Extraction of Multi-Energy Domain Reduced-Order Models Demonstrated on Capacitive MEMS Microphones

机译:电容式MEMS麦克风上演示的多能量域降阶模型的自动提取

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We present a methodology to systematically extract efficient and physically-based reduced-order models based on a mixed-level simulation approach and demonstrate its practicality for the design of a capacitive MEMS microphone. The method has been implemented in a MATLAB toolbox which starting from a FEM discretization, enables the automated generation of mixed-level VHDL-AMS based macro-models, which can be straightforwardly fed into a standard circuit simulator. The extracted models are highly efficient and moreover, in contrast to other equivalent network approaches, physically-based, thus allowing for the predictive simulation of microstructures with complex geometry.
机译:我们提出了一种基于混合级仿真方法来系统地提取高效且基于物理的降阶模型的方法,并论证了其在电容性MEMS麦克风设计中的实用性。该方法已在MATLAB工具箱中实现,该工具箱从FEM离散化开始,可以自动生成基于混合级VHDL-AMS的宏模型,可以直接将其输入到标准电路模拟器中。与其他等效的基于物理的网络方法相比,所提取的模型非常高效,并且因此可以对具有复杂几何形状的微结构进行预测性仿真。

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