Adaptive-Learning-Based Importance Sampling for Analog Circuit DPPM Estimation
Adaptive-Learning-Based Importance Sampling for Analog Circuit DPPM Estimation
复制标题
基于自适应学习的模拟电路 DPPM 估计重要性采样
DOI：
10.1109/mdat.2014.2361719
复制
发表时间：
2015
影响因子：
2
通讯作者：
S. Ozev
中科院分区：
文献类型：
--
作者：
E. Yilmaz;S. Ozev
本文探讨了缺陷等级估计这一重要问题。30多年来，已经发表了一些通常用于估计数字逻辑设计的零时刻测试逃逸率的模型。然而，估计模拟电路的逃逸率要困难得多。本文将重要性抽样技术应用于这一问题，得出了一种更实用的模拟缺陷等级计算方法。
This paper addresses the important problem of defect level estimation. For more than 30 years, there have been published models which are commonly used to estimate the time zero test escape rate of digital logic designs. However, estimating escape rate for analog circuits is much more challenging. This paper applies importance sampling techniques to this problem to arrive at a much more practical method of analog defect level computation.