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Discussion Starter #1
sorry for the nerd-out in advance but Im genuinely curious, mainly because my programmings skills and linear algebra are rusty.

Has anyone ever tired to use splines with some higher derivatives constraints to curve fitting and smooth their maps? were you successful? did it improve drivability?

I've been playing around with Matlab and treating my Alpha-N table as a topographical map, then creating a higher resolution grid to fit the data set to in an attempt to show relations between points. i've only tried liner regression and cubic splines so far but looking at a loess regression plus a few others in the slmengine add on.

Still haven't got a working program that spits out fitting values onto a fixed a array (e.g distinct RPM, TPS, or MAP points) but i do have a program that generates a nice fitted 3d curve. I figured i pose the question see if anyone else had any insight, or a code I might pillage ;)
 
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