[time-nuts] Dual Mixer
Steve Rooke
sar10538 at gmail.com
Wed May 12 11:22:32 UTC 2010
Sounds like someone is grandstanding to me!
Steve
On 12 May 2010 22:26, Bruce Griffiths <bruce.griffiths at xtra.co.nz> wrote:
> WarrenS wrote:
>>
>> Bruce
>>
>> Good, It does seem like we are finally making some good progress.
>> You now seem to acknowledge that my tester could work if I integrate.
>> You now seem to acknowledge that I am integrating by using a filter.
>
> In a sampled data system integration is equivalent to a filter but not just
> any arbitrary low pass filter.
> The errors in your method are explicitly spelled out in the paper I gave the
> link to:
> http://hal.archives-ouvertes.fr/docs/00/37/63/05/PDF/alaa_p1_v4a.pdf
> In this paper xi is a phase sample and yi is a frequency sample.
>>
>> I acknowledge that my integration method is not perfect, BUT it is simple
>> and good enough.
>
> Not yet proven nor quantified.
>>
>> It would seem the only issue left is to show you just how good of answers
>> my integration method gives.
>> At least now we are JUST talking about what the S/W needs to do.
>> Hopefully you now see that the hardware is adequate.
>> What would you consider an acceptable error band, 3 dB, 1 dB, 0.1 dB?
>> Pick a number >> zero.
>>
> The answer depends on how long one is willing to spend making the
> measurements.
> Certainly 0.1dB or better would require heroic efforts to demonstrate.
> Since the error will also depend on the phase noise spectra of the
> oscillators being compared a single figure answer isnt feasible.
> However for the case where white phase noise dominates the error should be
> not more than 1dB but potentially much less.
> The errors due to digital signal processing should be at least an order of
> magnitude lower.
>>
>> For a typical high speed data log taken at say 1 K samples per second, one
>> would generally run a quick test with maybe a minute's worth of data.
>> That would provide enough data to give a good tau plot up to about 10
>> seconds.
>
> That's a rather sweeping statement given that no estimates of the
> contribution to measurement noise due to the finite number of samples has
> been made.
> The maximum usable tau for a given record length depends on the maximum
> acceptable error due to the finite number of samples.
>>
>> Now if you can supply me with a 60K data log with any type of reasonably
>> typical noise that you want to include in it
>> I'll show you how close my approximate Integration comes to your perfect
>> integration.
>>
> You can't because your method of perfect integration isnt and its errors
> cannot be made sufficiently small with so few samples.
>
>> I can set this up to do as many times as you want, until I have
>> demonstrated by example that it is close enough,
>> for every data log case that you will provide. Near enough IS good enough
>> for me and most Nuts.
>
> Quantify near enough else all is just noise.
>>
>> As John pointed out, this is measuring noise. One is not going to get the
>> exact same answer twice in a row anyway.
>> My answer will not be perfect, but it will be simple and fast and easy and
>> below the noise uncertainty band.
>> Your turn to put a data log where your math is. Do try and remember I'm
>> working with Frequency and not phase.
>>
> Thats idle speculation as you havent quantified anything at all.
> The repeatability of the measurements needs to be quantified.
>>
>> BTW. just a heads-up warning to be fair. I have set up this situation so
>> that I can not loose.
>
> Its actually almost trivial to produce a set of samples for which any given
> method will fail.
> Doing so is an unproductive exercise.
>>
>> If you want to setup your own situation go for it. I'll see if I can do
>> it.
>> Only requirement is that it should be broken down into no more than 60K
>> sample sizes max for each test at the start.
>> After I pass that, if you want to go for millions of samples or whatever,
>> fine as long as I can read the text data log file.
>>
>> ws
>>
> Bruce
>
>
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--
Steve Rooke - ZL3TUV & G8KVD
A man with one clock knows what time it is;
A man with two clocks is never quite sure.
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