The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dans cet article, une nouvelle méthode d’extraction de corrélation spatiale intra-die appelée MLEMTC (Maximum Likelihood Estimation for Multiple Test Chips) est présentée. Dans la méthode MLEMTC, une fonction de vraisemblance conjointe est formulée en multipliant l'ensemble des fonctions de vraisemblance individuelles pour toutes les puces de test. Cette fonction de vraisemblance conjointe est ensuite maximisée pour extraire un groupe unique de valeurs de paramètres d'une fonction de corrélation spatiale unique, qui peut être utilisée pour l'analyse et la conception statistiques de circuits. De plus, pour traiter la composante purement aléatoire et l'erreur de mesure contenues dans les données de mesure, la fonction de corrélation spatiale combinée à la corrélation du bruit blanc est utilisée dans l'extraction, ce qui améliore considérablement la précision des résultats d'extraction. De plus, une technique basée sur la décomposition LU est développée pour calculer le déterminant log de la matrice définie positive dans la fonction de vraisemblance, ce qui résout le problème de stabilité numérique rencontré dans le calcul direct. Les résultats expérimentaux ont montré que la méthode proposée est efficace et pratique.
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Qiang FU, Wai-Shing LUK, Jun TAO, Xuan ZENG, Wei CAI, "Intra-Die Spatial Correlation Extraction with Maximum Likelihood Estimation Method for Multiple Test Chips" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 12, pp. 3007-3015, December 2009, doi: 10.1587/transfun.E92.A.3007.
Abstract: In this paper, a novel intra-die spatial correlation extraction method referred to as MLEMTC (Maximum Likelihood Estimation for Multiple Test Chips) is presented. In the MLEMTC method, a joint likelihood function is formulated by multiplying the set of individual likelihood functions for all test chips. This joint likelihood function is then maximized to extract a unique group of parameter values of a single spatial correlation function, which can be used for statistical circuit analysis and design. Moreover, to deal with the purely random component and measurement error contained in measurement data, the spatial correlation function combined with the correlation of white noise is used in the extraction, which significantly improves the accuracy of the extraction results. Furthermore, an LU decomposition based technique is developed to calculate the log-determinant of the positive definite matrix within the likelihood function, which solves the numerical stability problem encountered in the direct calculation. Experimental results have shown that the proposed method is efficient and practical.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.3007/_p
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@ARTICLE{e92-a_12_3007,
author={Qiang FU, Wai-Shing LUK, Jun TAO, Xuan ZENG, Wei CAI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Intra-Die Spatial Correlation Extraction with Maximum Likelihood Estimation Method for Multiple Test Chips},
year={2009},
volume={E92-A},
number={12},
pages={3007-3015},
abstract={In this paper, a novel intra-die spatial correlation extraction method referred to as MLEMTC (Maximum Likelihood Estimation for Multiple Test Chips) is presented. In the MLEMTC method, a joint likelihood function is formulated by multiplying the set of individual likelihood functions for all test chips. This joint likelihood function is then maximized to extract a unique group of parameter values of a single spatial correlation function, which can be used for statistical circuit analysis and design. Moreover, to deal with the purely random component and measurement error contained in measurement data, the spatial correlation function combined with the correlation of white noise is used in the extraction, which significantly improves the accuracy of the extraction results. Furthermore, an LU decomposition based technique is developed to calculate the log-determinant of the positive definite matrix within the likelihood function, which solves the numerical stability problem encountered in the direct calculation. Experimental results have shown that the proposed method is efficient and practical.},
keywords={},
doi={10.1587/transfun.E92.A.3007},
ISSN={1745-1337},
month={December},}
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TY - JOUR
TI - Intra-Die Spatial Correlation Extraction with Maximum Likelihood Estimation Method for Multiple Test Chips
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 3007
EP - 3015
AU - Qiang FU
AU - Wai-Shing LUK
AU - Jun TAO
AU - Xuan ZENG
AU - Wei CAI
PY - 2009
DO - 10.1587/transfun.E92.A.3007
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 12
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - December 2009
AB - In this paper, a novel intra-die spatial correlation extraction method referred to as MLEMTC (Maximum Likelihood Estimation for Multiple Test Chips) is presented. In the MLEMTC method, a joint likelihood function is formulated by multiplying the set of individual likelihood functions for all test chips. This joint likelihood function is then maximized to extract a unique group of parameter values of a single spatial correlation function, which can be used for statistical circuit analysis and design. Moreover, to deal with the purely random component and measurement error contained in measurement data, the spatial correlation function combined with the correlation of white noise is used in the extraction, which significantly improves the accuracy of the extraction results. Furthermore, an LU decomposition based technique is developed to calculate the log-determinant of the positive definite matrix within the likelihood function, which solves the numerical stability problem encountered in the direct calculation. Experimental results have shown that the proposed method is efficient and practical.
ER -