基于离散希尔伯特变换的DRAM封装模型因果关系强化新方法

H. Aboutaleb, L. L. Baranny, A. Elshabini, F. Barlow
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引用次数: 5

摘要

因果关系验证和执行是生成高速电气包宏观模型的重要步骤,它通常分两个步骤完成:将测量的系统参数向量拟合成有理函数表示,然后执行希尔伯特变换积分来检查并在需要时执行因果关系。这个过程受到各种近似、截断和离散误差的影响。此外,测量或模拟的系统数据仅在有限带宽上已知,而希尔伯特变换必须在无限域上计算。为了避免这些误差以及传递函数外推到无穷远时的不准确性,提出了一种新的方法来检查和加强因果关系,即使用多项式插值周期性扩展的原始带限数据,并通过精确FFT计算周期性扩展数据的希尔伯特变换。
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A new method for causality enforcement of DRAM package models using discrete hilbert transforms
Causality verification and enforcement is an essential step in generating high speed electric package macromodels and it often accomplished in two steps: vector fitting measured system parameters into a rational function representation and then performing the Hilbert Transform integrations to check and if needed enforce causality. This procedure suffers from various approximation, truncation, and discretization errors. Besides, the measured or simulated system data are known only on the finite bandwidth, while the Hilbert Transform has to be computed on the infinite domain. To avoid these errors as well as inaccuracy of extrapolation of the transfer function to infinity, a new method is proposed to check and enforce causality by using raw bandlimited data that is extended periodically using a polynomial interpolation and computing the Hilbert Transform of the periodically extended data via accurate FFT.
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Comparison of passive enforcement techniques for DRAM package models Welcome to the 2013 IEEE WMED A new method for causality enforcement of DRAM package models using discrete hilbert transforms Invited talk: Computing beyond the 11nm node: Which devices will we use? Invited tutorial: Channel equalization: Techniques for high-speed electrical links
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