Efficient Spatial Pattern Analysis for Variation Decomposition Via Robust Sparse Regression

Efficient Spatial Pattern Analysis for Variation Decomposition Via Robust Sparse Regression

In this paper, we propose a new technique to achieve accurate decomposition of process variation by efficiently performing spatial pattern analysis. We demonstrate that the spatially correlated systematic variation can be accurately represented by the linear combination of a small number of template...

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Bibliographic Details
Main Authors: Zhang, Wangyang (Author), Balakrishnan, Karthik (Contributor), Li, Xin (Author), Boning, Duane S. (Contributor), Saxena, Sharad (Author), Strojwas, Andrzej (Author), Rutenbar, Rob A. (Author)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Microsystems Technology Laboratories (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2014-12-22T15:41:06Z.
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