User`s guide

Pattern
Marker
Data
Pattern
∆
t
1
∆
t
2
∆
t
3
∆
t
4
∆
t
5
∆
t
6
∆
t
7
∆
t
8
∆
t
9
∆
t
10
∆
t
11
∆
t
12
∆
t
13
Lastly, data is gathered to show PJ and RJ frequency components. PJ and RJ components are
determined by taking the variance of timing measurements from the histogram at each UI. The variance
is the square of the standard deviation of the histogram at each UI. If any "holes" in the variance record
exists, they will be interpolated by either a cubic or linear fit. The plot of the variance versus UI (1-Sigma
view) is the autocorrelation of the periodic and random jitter. Refer to the "High Frequency Modulation"
Getting Started Guide for further information about this concept.
An FFT of the autocorrelation function is used to determine the periodic components. The Fast Fourier
transform of the autocorrelation function is commonly referred to as the power spectral density or power
spectrum. The largest magnitude periodic component represents the PJ contribution to TJ. The RJ
component is determined by subtracting the spectral components, summing the background then taking
the square root to provide a 1-sigma value.
Pattern
Marker
Data
Pattern
Optionally, TailFit allows the accurate determination of random jitter when there is a significant amount of
periodic jitter. Refer to Histogram Getting Started Guide for more about TailFit and RJ.
Section 4 - GigaView © WAVECREST Corporation 2005
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