The 3D noise model is a white noise approximation consisting of 7 independent contributions that span the 3D correlation space (1 one dimensional uncorrelated processes, 3 two dimensional uncorrelated processes, and one three dimensional uncorrelated process). These scripts allow the user to simulate a noise cube, calculate the 7 independent variances, and calculate the confidence intervals. An additional script provides examples of how the functions can be called under different circumstances, for example correcting a past measurement, or iteratively calculating the noise cube by chunking the data.
This code is in support of a journal article "Finite Sampling Corrected 3D Noise with Confidence Intervals" https://www.osapublishing.org/ao/abstract.cfm?uri=ao-54-15-4907
David Haefner (2020). Finite Sampling Corrected 3D Noise with Confidence Intervals (https://www.mathworks.com/matlabcentral/fileexchange/49657-finite-sampling-corrected-3d-noise-with-confidence-intervals), MATLAB Central File Exchange. Retrieved .
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