PA-Paul Posted August 30, 2017 Report Share Posted August 30, 2017 Hi All, This may be a maths question, or a computer science question... or both. We have a device frequency response data set, which is measured at discrete frequency intervals, typically 1 MHz. For one particularly application, we need to interpolate that down to smaller discrete intervals, e.g. 50 kHz. We've found that the cubic Hermite interpolation works pretty well for us in this application. Whilst doing some testing of our application, I came across an issue which is arguably negligible, but I'd like to understand the origins and the ideal solution if possible. So - If i interpolate my data set with my X values being in MHz and create my "xi" data set to be in MHz and with a spacing of 0.05, I get a different result from the interpolation VI than I do if I scale my X data to Hz and create my xi array with a spacing of 50,000. The difference is small (very small), but why is it there in the first place? I assume it comes from some kind of floating point precision issue in the interpolation algorithm... but is there a way to identify which of the two options is "better" (i.e. should I keep my x data as frequency and just scale to MHz for display purposes when needed, or should I keep it in MHz)? Ideologically there should be no difference - in both cases I'm asking the interpolation algorithm to interpolate "by the same amount" (cant think of the write terminology there to say we're going to 1/20th of the original increment in both cases). Attached is a representative example of the issue (In LV 2016)... Thanks in advance for any thoughts or comments on this! Paul Interpolation with Hz and MHz demo.vi Quote Link to comment
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