Hi, all I'm simulating some noise to try to improve my somewhat sketchy understanding of what goes on with the various noise types as shown on an ADEV plot. Nothing fancy, ~3600 points of gaussian random numbers between 0 and 1 in excel, imported into Timelab as phase data, scaled to ns.
I mostly get what I expect; "pure" random noise, gives the expected slope for W/F PM, -1. Integrating the same random data gives the expected slope for W FM -1/2. Integrating the same random data yet again gives a slope of +1/2, again as expected for RW FM. However, looking at the data, I am somewhat baffled by a difference in the starting point of the slopes. Given that this is exactly the same random sequence, I would expect the curves to have the same startingpoint at tau0.. Clearly not (see attached), but I do not understand why. Any clues? Is this some elemental effect of integration (sqrt(n) or some such), or am I seeing the effects of bandwidth and/or bias-functions or other esoterica? In case the screenshot does not make it though; W PM starts at 1.69e-9 W FM starts at 9.74e-10 RW FM starts at 6.92e-10 Thanks for any help! Ole
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