10-19-2010 10:43 AM - edited 10-19-2010 10:44 AM
Hello,
I experienced a limitation using Lagrange interpolation,
I can only use a vector of max 13 values for correct interpolation,
this problem does not appear with nearest, linear, spline, or hermite cubic methods.
Best R.
Nicolas
Solved! Go to Solution.
10-20-2010 02:57 AM
Have you experienced the same problem ?
10-20-2010 03:12 AM
I tested the LV example:
labview\examples\analysis\intpxmpl.llb
In fact, there is the same problem with dataset 3 where there is greater than 13 control keys.
The curve has a strange behaviour with a huge peak that downscale all the others near a zero looking value.
This may be the mathematical law which is limited ?
Nicolas
10-20-2010 03:51 AM
Ok I think I find the solutionon wikipedia Lagrange:
"Lagrange and other interpolation at equally spaced points, as in the example above, yield a polynomial oscillating above and below the true function. This behaviour tends to grow with the number of points, leading to a divergence known as Runge's phenomenon; the problem may be eliminated by choosing interpolation points at Chebyshev nodes."
Hope it helps you.
Nicolas