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Jitter, Noise, and Signal Integrity at High-Speed by Mike Peng Li

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5. Jitter and Noise Separation and Analysis in the Statistical Domain

This chapter focuses on jitter separation methods in the statistical domain. First we discuss why jitter separation is necessary, as far as its value and benefits, in terms of understanding and practical application. Then we discuss jitter separation methods given jitter process observables of PDF and CDF. The well-known and widely used Tailfit method[1] is covered in detail. Last, we discuss the dual-Dirac model DJ PDF and its accuracy.

5.1. Rationale and Motivation for Jitter Separation

This section discusses the motivations and reasons for separating jitter into its various components. First we discuss the need for jitter separation, from the points of view of understanding, ...

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