Matlab Function Fitting: Tips & Tricks

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SUMMARY

Fitting data in MATLAB can be effectively achieved using the polyfit function, particularly when dealing with exponential decay by applying logarithmic transformations. Users have reported that fminspleas is another useful tool for optimization in fitting functions. The discussion emphasizes the importance of selecting the right fitting method based on the data characteristics and the desired model. Overall, MATLAB provides robust functions for data fitting, making it a preferred choice for many users.

PREREQUISITES
  • Familiarity with MATLAB programming environment
  • Understanding of data fitting concepts
  • Knowledge of logarithmic transformations
  • Experience with optimization techniques in MATLAB
NEXT STEPS
  • Explore the polyfit function in MATLAB for polynomial fitting
  • Learn about fminspleas for optimization in function fitting
  • Research exponential decay models and their applications
  • Investigate the use of lsqcurvefit for nonlinear curve fitting in MATLAB
USEFUL FOR

This discussion is beneficial for data analysts, researchers, and engineers who utilize MATLAB for data fitting and modeling, particularly those working with exponential decay data.

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Hello all,

How do people generally fit data in Matlab? I am trying to fit an exponential decay and it doesn't look straightforward. I am looking this up at the moment, but maybe people can give me good answers or starting points here.

Thank you!
 
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Think this is fminspleas
 
I usually use polyfit with the appropriate logarithms.
 

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