Jitter analysis based on kernel density estimation and dual-dirac

Accurate jitter analysis is critical for next-generation I/O designs. In this paper, a method to separate deterministic jitter (DJ) and random jitter (RJ) is proposed, which first obtains the Time Interval Error (TIE) histogram of the signal, then uses the Kernel Density Estimation (KDE) algorithm to smooth the histogram, and then defines a fitting parameter to perform a Dual-Dirac fit on the smoothed histogram to estimate DJ and RJ. Finally, the estimation results of the method are given, and the estimation errors of deterministic jitter and random jitter are 1.2% and 4.7%, respectively, which verifies the effectiveness of the method.