Area Normalized 1D Supergaussian and Fitting Noisy Data
Function creates an area normalized supergaussian for user input coordinates and center point, size at max/e (width), and supergaussian P value.
Another function shows how to fit noisy data to a supergaussian. First, estimate area, width, and center point. Then find minimum values for a sweep of possible supergaussian integers. The solution is the best of the best fit.
The fitting demo, uses the imnoise function of the image toolbox. This can be commented out to use just regular random noise..
Cite As
Meg Noah (2024). Area Normalized 1D Supergaussian and Fitting Noisy Data (https://www.mathworks.com/matlabcentral/fileexchange/88461-area-normalized-1d-supergaussian-and-fitting-noisy-data), MATLAB Central File Exchange. Retrieved .
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Version | Published | Release Notes | |
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1.0.0 |