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Estimation of jitter and eye diagram in high-speed serial channels can be challenging. The existing methods might fail to show inter-symbol interference (ISI) and data dependent jitter because they are either excessively time consuming or only applicable to linear time-invariant (LTI) systems. Therefore, this paper suggests a hybrid methodology to develop surrogate models of the system from a short transient simulation and using them to efficiently determine the eye diagram and related parameters. This paper is based on uncertainty quantification techniques that use polynomial chaos (PC) expansions to estimate the output. Necessary modifications are applied to PC modeling to make it applicable to high-speed channels. Finally, the performance of the proposed approach is shown through numerical examples. INDEX TERMS Signal integrity, eye diagram, jitter, high-speed channel, machine learning, polynomial chaos, statistical analysis.

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