Spatial variation decomposition via sparse regression

Spatial variation decomposition via sparse regression

In this paper, we briefly discuss the recent development of a novel sparse regression technique that aims to accurately decompose process variation into two different components: (1) spatially correlated variation, and (2) uncorrelated random variation. Such variation decomposition is important to i...

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Bibliographic Details
Main Authors: Zhang, Wangyang, Balakrishnan, Karthik, Li, Xin, Acar, Emrah, Liu, Frank, Rutenbar, Rob A., Boning, Duane S.
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:en_US
Published: Institute of Electrical and Electronics Engineers (IEEE) 2014
Online Access:http://hdl.handle.net/1721.1/92427
https://orcid.org/0000-0002-0417-445X

Internet

http://hdl.handle.net/1721.1/92427
https://orcid.org/0000-0002-0417-445X

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