A Hierarchical Statistical Optimization Method Driven by Constraint Generation Based on Mahalanobis' Distance(Special Section of Selected Papers from the 13th Workshop on Circuits and Systems in Karuizawa)

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概要

• 論文の詳細を見る

• This paper presents a method of statistical system optimization. The method uses a constraint generation, which is a design methodology based on a hierarchical top-down design, to give specifications to sub-circuits of the system. The specifications are generated not only to reduce the costs of sub-circuits but also to take adequate margin to achieve enough yield of the system. In order to create an appropriate amount of margin, a term which expresses a statistical figure based on Mahalanobis' distance is added to the constraint generation problem. The method is applied to a PLL, and it is confirmed that the yield of the lock-up time reaches 100% after the optimization.

• 2001-03-01

著者

• Fujita Tomohiro

  Department of Biomolecular Science, Faculty of Science, Toho University

• Onodera Hidetoshi

  Department Of Communications And Computer Engineering Graduate School Of Informatics Kyoto Universit

• Fujita Tomohiro

  Department Of Biomolecular Science Faculty Of Science Toho University

• Fujita Tomohiro

  Department Of Communications And Computer Engineering Graduate School Of Informatics Kyoto Universit

• Onodera Hidetoshi

  Department of Communication and Computer Engineering, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan

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