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- Resampling
- Spline approximation
- Douglas Peucker approximation
- Median filter
- Gliding Moving average filter
- Fourier low pass filter
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The other group of methods is the gliding moving average steepness algorithms. These algorithms compute the average steepness at an interval to the left and right of each point on the line, and compares these two steepnesses in order to compute the change of gradient. These methods are not as sensitive to noise as the finite difference methods. Therefore, you usually do not need to smoothen the input data when using this algorithm. The algorithm will get less and less sensitive to noise in the input data as you increase the calculation interval.
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