Characterizing Intra-Die Spatial Correlation Using Spectral Density Fitting Method
Characterizing Intra-Die Spatial Correlation Using Spectral Density Fitting Method
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DOI：
10.1587/transfun.e92.a.1652
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发表时间：
2009-07
期刊：
影响因子：
--
通讯作者：
Qiang Fu;W. Luk;Jun Tao;Changhao Yan;Xuan Zeng
中科院分区：
文献类型：
--
作者：
Qiang Fu;W. Luk;Jun Tao;Changhao Yan;Xuan Zeng
本文提出了一种用于芯片内空间相关函数提取的谱域方法--谱密度拟合法。在对随机场进行理论分析的基础上，利用谱密度作为相关函数的谱域对应，在谱域中有效地估计了相关函数的参数。与已有的原始空域提取算法相比，SDF方法在谱域可以获得相同质量的结果。在实际测量过程中，不可避免的具有任意频率分量的测量误差会极大地影响提取结果。进一步发展了一种滤波技术，以消除测量误差的高频分量，并从噪声污染中恢复数据用于参数估计。实验结果表明，SDF方法具有较好的实用性和稳定性。
In this paper, a spectral domain method named the SDF (Spectral Density Fitting) method for intra-die spatial correlation function extraction is presented. Based on theoretical analysis of random field, the spectral density, as the spectral domain counterpart of correlation function, is employed to estimate the parameters of the correlation function effectively in the spectral domain. Compared with the existing extraction algorithm in the original spatial domain, the SDF method can obtain the same quality of results in the spectral domain. In actual measurement process, the unavoidable measurement error with arbitrary frequency components would greatly confound the extraction results. A filtering technique is further developed to diminish the high frequency components of the measurement error and recover the data from noise contamination for parameter estimation. Experimental results have shown that the SDF method is practical and stable.