2026-09-21T02:43:18Zhttps://api.mountainscholar.org/server/oai/request

oai:mountainscholar.org:10217/1767222025-12-30T03:31:14Zcom_10217_100532com_10217_100000com_10217_100411com_10217_100303col_10217_100538col_10217_100415

Ahadi Dolatsara, Majid, author Roy, Sourajeet, advisor Notaros, Branislav, committee member Anderson, Chuck, committee member Pezeshki, Ali, committee member 2016-08-18T23:10:23Z 2016-08-18T23:10:23Z 2016 AhadiDolatsara_colostate_0053N_13762.pdf http://hdl.handle.net/10217/176722 https://doi.org/10.25675/3.018747 With the scaling of VLSI technology to sub-45 nm levels, uncertainty in the nanoscale manufacturing processes and operating conditions have been found to result in unpredictable circuit behavior at the chip, package, and board levels of modern integrated microsystems. Hence, modeling the forward propagation of uncertainty from the device-level parameters to the system-level response of high-speed circuits and systems forms a crucial requirement of modern computer-aided design (CAD) tools. This thesis presents novel approaches based on the generalized polynomial chaos (gPC) theory for the efficient multidimensional uncertainty quantification of general distributed and lumped high-speed circuit networks. The key feature of this work is the development of approaches which are more efficient and/or accurate comparing to recently suggested uncertainty quantification approaches in the literature. Main contributions of this thesis are development of two individual approaches for improvement of the conventional linear regression uncertainty quantification approach, and development of a sparse polynomial expansion of the stochastic response in an uncertain system. The validity of this work is established through multiple numerical examples. born digital masters theses English eng Colorado State University. Libraries 2000-2019 Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. high speed circuits polynomial chaos uncertainty quantification linear regression computer aided design signal integrity Efficient multidimensional uncertainty quantification of high speed circuits using advanced polynomial chaos approaches Text Master of Science (M.S.) Masters Electrical and Computer Engineering Colorado State University This Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). open.access