多元自适应回归样条在半导体纳米技术标准细胞表征中的应用

Taizhi Liu
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引用次数: 4

摘要

多元自适应样条回归(MARSP)是一种非参数回归方法。它是一种不存在任何预定回归模型的自适应过程。因此,MARSP的模型结构是根据从数据中获取的信息动态自适应地构建的。由于它能够捕获基本的非线性和相互作用,MARSP被认为非常适合于高维问题。本章给出了MARSP在半导体领域的应用,特别是在标准电池表征方面的应用。标准细胞表征的目标是创建一组高质量的标准细胞库模型,以准确有效地捕获细胞行为。在本章中,采用MARSP方法将门延迟表征为许多参数的函数,包括工艺电压-温度参数。由于MARSP方法能够捕获重要的非线性和相互作用,有助于显著提高精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multivariate Adaptive Regression Splines in Standard Cell Characterization for Nanometer Technology in Semiconductor
Multivariate adaptive regression splines (MARSP) is a nonparametric regression method. It is an adaptive procedure which does not have any predetermined regression model. With that said, the model structure of MARSP is constructed dynamically and adaptively according to the information derived from the data. Because of its ability to capture essential nonlinearities and interactions, MARSP is considered as a great fit for high-dimension problems. This chapter gives an application of MARSP in semiconductor field, more spe -cifically, in standard cell characterization. The objective of standard cell characterization is to create a set of high-quality models of a standard cell library that accurately and efficiently capture cell behaviors. In this chapter, the MARSP method is employed to characterize the gate delay as a function of many parameters including process-voltage-temperature parameters. Due to its ability of capturing essential nonlinearities and inter- actions, MARSP method helps to achieve significant accuracy improvement.
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