Polynomial Chaos modeling for jitter estimation in high-speed links

Majid Ahadi Dolatsara, Huan Yu, Jose Ale Hejase, Wiren Dale Becker, Madhavan Swaminathan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


Determination of the data dependent jitter and its effect on the eye diagram is a challenging task in modern high-speed links; therefore, novel statistical approaches are required to expedite this task. Most of the current methods for jitter estimation are only applicable to linear systems, while nonlinear components play an essential role in the high-speed link response. Therefore, this paper introduces a new data dependent jitter estimation approach by using stochastic analysis. In this approach generalized Polynomial Chaos theory is utilized, where linear regression is used to create surrogate models for the link. Statistics of the output signal and jitter calculation are then directly obtained from these models. Two numerical examples are provided to evaluate the efficiency and accuracy of the proposed approach showing good match with the traditional transient eye analysis with good speedup.

Original languageEnglish (US)
Title of host publicationInternational Test Conference 2018, ITC 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538683828
StatePublished - Jul 2 2018
Event49th IEEE International Test Conference, ITC 2018 - Phoenix, United States
Duration: Oct 29 2018Nov 1 2018

Publication series

NameProceedings - International Test Conference
ISSN (Print)1089-3539


Conference49th IEEE International Test Conference, ITC 2018
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Applied Mathematics


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