fmincon instead of lsqcurvefit
3 Ansichten (letzte 30 Tage)
Ältere Kommentare anzeigen
Mohammad Nidal
am 27 Feb. 2021
Bearbeitet: Matt J
am 2 Mär. 2021
options = optimoptions(@lsqcurvefit,'Algorithm','levenberg-marquardt','MaxIter',10000,'TolX',1e-12);
[p,resnorm,res,EXITFLAG,OUTPUT,LAMBDA,jocob]=lsqcurvefit(@fun725,p0,time,x,pL,pU);
While using this we are not getting proper value. How can we implement 'fmincon' or someother optimisation tools.
1 Kommentar
Star Strider
am 27 Feb. 2021
Note that ‘proper value’ is a matter of interpretation. It depends on what ‘fun725’ is, how you wrote it, and what initial parameter estimates you provided.
Some of the Global Optimization Toolbox functions can search the entire parameter space for the best parameter set, so using it would likely be appropriate.
Akzeptierte Antwort
Shadaab Siddiqie
am 2 Mär. 2021
If the problem is data fitting, then you should use 'lsqcurvefit' if possible. If the problem has nonlinear constraints, then see the random discussion.
if the problem is to find minimum, then you should use 'fmincon' if possible. It workes for nonlinear multivariable function.
0 Kommentare
Weitere Antworten (0)
Siehe auch
Kategorien
Mehr zu Nonlinear Optimization finden Sie in Help Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!