Introducing Gaussian errors to data (Matlab)

AI Thread Summary
To introduce Gaussian errors to velocity measurements in MATLAB, the user needs to generate random Gaussian noise with a mean of zero and a standard deviation of 0.2. The attempt to use the imnoise command was inappropriate, as it is designed for image data and resulted in values not aligning with the original velocity data. Instead, the user should utilize the randn function to create Gaussian noise and then add it to the velocity measurements. This approach ensures that the added noise maintains the desired statistical properties. Proper implementation will yield velocity values that reflect the intended Gaussian errors.
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Homework Statement



I need to introduce Gaussian errors to a set of velocity measurements. The errors should have mean zero and standard deviation .2.
v = [4.6 3.8 7.2 9.7 6.4];

The Attempt at a Solution



I tried to use Matlab's imnoise command (J=imnoise(v,'gaussian',0,.04), but based on the answers I got, I think that this was not the appropriate approach to this problem (the answers are all between 0 and 1, not close to the original velocity data).
 
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