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Accurate and Scalable IO Buffer Macromodel Based on Surrogate Modeling

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3 Author(s)
Ting Zhu ; Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA ; Steer, M.B. ; Franzon, P.D.

In this paper, a new method is proposed to generate accurate and scalable macromodels for input/output buffers. The method characterizes the physically based model elements with adaptive multivariate surrogate modeling techniques in order to achieve high fidelity and process-voltage-temperature scalability. Both single-ended and differential output buffer circuit examples demonstrate that the proposed modeling method offers good accuracy and flexible scalability to facilitate signal integrity analysis.

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Components, Packaging and Manufacturing Technology, IEEE Transactions on  (Volume:1 ,  Issue: 8 )