2026-09-19T04:57:07Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/72778 2023-07-11 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Cangellaris, Andreas C. Schutt-Ainé, José E. Chen, Xu 2015-01-21T19:48:05Z 2015-01-21T19:48:05Z 2014-12 2015-01-21 2014-12 As speed and density of electronic systems continue to increase, uncertainties are becoming significant factors in system performance. This thesis provides an overview of stochastic numerical techniques in the context of electronic package modeling for signal integrity analysis. Examples are provided to demonstrate the efficiency and accuracy of the Stochastic Collocation method, and its application in computer system design optimization. A stochastic Finite Element Method electromagnetic solver is also implemented using Stochastic Collocation to study waveguides with geometric uncertainties. Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2014-12-03T20:24:43Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Chen_Xu.pdf: 3494456 bytes, checksum: 58998182faa14b98321d958b70f7e17d (MD5) Made available in DSpace on 2015-01-21T19:48:05Z (GMT). No. of bitstreams: 1 Xu_Chen.pdf: 3494456 bytes, checksum: 58998182faa14b98321d958b70f7e17d (MD5) http://hdl.handle.net/2142/72778 en Copyright 2014 Xu Chen signal integrity stochastic computational electromagnetics waveguide optimization finite element method packaging modeling simulation Numerical methods stochastic collocation monte carlo uncertainty quantification modal signaling Stochastic techniques for computational electromagnetics and signal integrity design optimization text Electrical & Computer Eng 1933 Electrical & Computer Engr 1200 University of Illinois at Urbana-Champaign Thesis M.S. MS:Electr & Computer Eng-UIUC 10KS1200MS