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A guaranteed-convergence framework for passivity enforcement of linear macromodels

机译:线性宏模型的被动实施的保证收敛框架

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摘要

Passivity enforcement is a key step in the extraction of linear macromodels of electrical interconnects and packages for Signal and Power Integrity applications. Most state-of-the-art techniques for passivity enforcement are based on suboptimal or approximate formulations that do not guarantee convergence. We introduce in this paper a new rigorous framework that casts passivity enforcement as a convex non-smooth optimization problem. Thanks to convexity, we are able to prove convergence to the optimal solution within a finite number of steps. The effectiveness of this approach is demonstrated through various numerical examples.
机译:无源性强制是提取用于信号和电源完整性应用的电气互连和封装的线性宏模型的关键步骤。大多数用于被动执行的最新技术都是基于不能保证收敛的次优或近似公式。我们在本文中介绍了一个新的严格框架,该框架将无源强制性强制转换为凸的非平滑优化问题。由于凸性,我们能够在有限的步骤内证明收敛到最优解。通过各种数值示例证明了该方法的有效性。

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