How to do "Cosine wave approximation“ for random plot data
1 visualizzazione (ultimi 30 giorni)
Mostra commenti meno recenti
ryohei yanagawa
il 21 Dic 2018
Commentato: ryohei yanagawa
il 22 Dic 2018
I want to do "Cosine wave approximation“ for randam plot data.
Is there a way to forcefully approximate the following data?
Also please tell me about how to do it.
x = [0.087266463 0.261799388 0.436332313 0.610865238 0.785398163 0.959931089 1.134464014 1.308996939 1.483529864];
y = [22 22 16 13 13 9 3 0 3];
0 Commenti
Risposta accettata
John D'Errico
il 21 Dic 2018
easy peasy. Though I have no clue what it means to "forcef\ully approximate".
x0 = [mean(y),max(y) - min(y)/2,0,3];
ft = fittype('a + b*cos((x-c)*d)')
ft =
General model:
ft(a,b,c,d,x) = a + b*cos((x-c)*d)
mdl = fit(x',y',ft,'startpoint',x0)
mdl =
General model:
mdl(x) = a + b*cos((x-c)*d)
Coefficients (with 95% confidence bounds):
a = 11.96 (7.416, 16.51)
b = 10.43 (4.97, 15.88)
c = -0.02594 (-0.8867, 0.8348)
d = 2.079 (0.141, 4.017)
plot(x,y,'o'),hold on,plot(mdl)
5 Commenti
John D'Errico
il 21 Dic 2018
If I had to guess, you are trying to execute lines of command window output from the curve fitting toolbox.
I would strongly suggest that you read the documentation for the curve fitting toolbox. It also looks like you want to read the getting started tutorialsin MATLAB, since it looks like you are trying to execute things that are not MATLAB code.
Più risposte (0)
Vedere anche
Categorie
Scopri di più su Sources in Help Center e File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!