Mmmm yes you can see the equation evaluation starting to rise in your
"Warmer" plot, as Mark says, which will make a nonsense of the formula if
your summer temps get above 28.
Why not a table and then interpolate between the table data points?. You
might have more points where the changes are greater.
The colder plot looks cubic maybe for a crystal made for 20 deg C ?? But
depending on the oscillator electronics you may have component tempcos
affecting the frequency as well?
I suspect the turnover at 21deg C should be a smooth curve not as your
formula predicts. Which suggests that you have too too high an order of
polynomial I think, but you may not get a good fit with a cubic if other
effects are present.
Alan
G3NYK
----- Original Message -----
From: "Dan Drown" <[email protected]>
To: <[email protected]>
Sent: Saturday, November 01, 2014 10:07 PM
Subject: Re: [time-nuts] Digital temperature compensation
I gave zunzun a try and the one with the lowest root mean squared error
was:
f(x) = a( x**0.5) + b( x ) + c( sin(x) ) + d( cos(x) )
It got 0.202 RMSE, so I guess I'll stick with my original function as it
seems to be closer to what I expect will happen at colder/hotter temps.
You have a good point about temperatures outside my data samples. Once
it gets hot again in the summertime, I'm sure I'll have to re-evaluate
this.
Quoting Mark Sims <[email protected]>:
You could try submitting your data to zunzun.com It will fit it to
around 40,000 different curves and find the best ones.
Beware that with all curve fitting formulas, once your live data starts
to wander out of the range of your original curve fit data, things can
go rather badly...
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