interpolation - Scaling/Interpolating measure data in C# -

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First of all, if I ask for apologies before asking questions, but about 10 hours on each link in intensive research Google offered every single phrase to me, I could not find anything that would help me with my problem.

What I want to do is the following:

  1. Recover two excel sheets with data from two different scientific measurements. Such information in each sheet Which can be easily compared to the second sheet, respectively. The difference between the two sheets is only the amount of data points that they contain. for example : The first sheet has a time of 200 seconds, in which there is a point representing 1 second. In the second sheet, there is also a point representing a second time span, 0.5 seconds for but .

  2. The problem I solved is that the sheet "scale" with less data points can be easily compared in a way so that each row in the chart is on the x-axis Could use the same place.

    The problem with this task is that there is a lack of sufficient mathematical background to create algorithms in IM.

    I have already created the entire application with a GUI, smoothing with the average import and running of axle sheets (only useful if the same length of dataset is the same).

    Any place or link to any place where it can be explained is welcome.

    I also want to say that any code which I currently have is totally irrelevant to this question, it is about an additional method with functionality.

    In advance, the morphic

    If there is a direct connection between the data points of both sets Correlation - that is, the time is matched for both - so it can be enough to make a linear interpolation on a small set to generate missing digits. For example, the first set of data is: 

      Time value 12: 00: 00.0 100.0 12: 00: 01.0 120.0 12: 00: 02.0 117.5   
     ... and your second set looks like this:  
      Time value is 12: 00: 00.0 2.5 12: 00: 00.5 3.0 12: 00: 01.0 2.6 12: 00: 01.5 2.9 12: 00: 02.0 2.8   
     Based on what we are trying to do with the data later, we can fill the gap in the first list in some ways.  
     To make a linear interpolation of the simplest values, if your points are identical to the value you are looking for (i.e.: you are finding value at half way point), then just join them together to find missing points Add to:  
      Time value leap 12: 00: 00.0 100.0 12: 00: 00.5 110.0 12: 00: 01.0 120.0 12: 00: 01.5 118.75 12: 00: 02.0 117.5   
     This is fine if the sample rate is high enough in relation to the rate on which the input is different. I have seen several audio processing algorithms that use this type of calculation to double the sample rate. When you do not have very high frequency data with sampling rates, which is good for capturing the infection Are very few  
     The second option is to use a bar function to fit a curve against the series of points, then synthesize the missing points in the form of the offset on the curve. This will give you smooth and more natural interpolation, with the hump in the data looks more realistic. If the time between the data set is not properly aligned, it will also give you a very good way to offset your data - calculate each point as the offset with the curve along the distance of the time offset there There are lots of spell implementations you can use for it. I suggest Catmouth-Rome as an early algorithm.  
      Warning:  If you are doing some sort of statistical analysis on the output, you  not  are going to get good results by doing this, regardless of How do you do it    If your goal is your group, then cut down a large group instead of creating data in small groups.

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