Function Analysis: Example 3
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Description How it works Examples: Reaction Kinetics 1-D Random Walk Analysis of Noisy Data |
Analysis of Noisy DataIn many engineering and scientific studies, data is obtained from a system or process using sensors. These data typically contain noise. In this example, we look at the difficulty of fitting this data to a differential model using numerical differentiation.The function we plot is =RAND() from 0 to 1, the constant of integration is 0. This function simulates random noise on a DC signal of magnitude 0.5. The plot of the function looks like this:  The first derivative of the data is shown below:  Note that the derivative is even noisier than the source data. In comparison, the integral plot is smoother. It is close to a straight line with slope = 0.5, suggesting that it might be better to look at the integral of the data to look for underlying structure.  |