A Bayesian-based process parameter estimation using IDDQ current signature

Michihiro Shintani, Takashi Sato
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引用次数: 7

Abstract

Post-fabrication performance compensation and adaptive delay testing are effective means to improve yield and reliability of LSIs. In these methods, process parameter estimation plays a key role. In this paper, we propose a novel technique for accurate on-chip process parameter estimation. The proposed technique is based on Bayes' theorem, in which on-chip parameters, such as threshold voltages, are estimated by current signatures obtained within a regular IDDQ testing. No additional circuit and additional measurements are required for the purpose of estimation. Numerical experiments demonstrate that the proposed technique can achieve less than 10 mV accuracy in estimating threshold voltages.
基于贝叶斯的IDDQ电流签名过程参数估计
后期性能补偿和自适应延迟测试是提高lsi成品率和可靠性的有效手段。在这些方法中,过程参数估计起着关键作用。在本文中,我们提出了一种精确的片上工艺参数估计的新技术。所提出的技术是基于贝叶斯定理,其中芯片上的参数,如阈值电压,是通过在常规IDDQ测试中获得的电流特征来估计的。不需要额外的电路和额外的测量来进行估计。数值实验表明,该方法对阈值电压的估计精度可以达到小于10 mV。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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