Trouble with Envelope Functions

9 visualizzazioni (ultimi 30 giorni)
Si
Si il 21 Apr 2015
Commentato: Hany Ferdinando il 29 Gen 2019
Hi,
I have been trying to obtain a smooth envelope of my data. I have tried using other peoples solutions from the file exchange but unable to get a smooth envelope. See attached images.
Attached is the relevant data.
If anyone can recommend a file exchange or other solution would be much appreciated!
Thanks!
  1 Commento
Glo
Glo il 21 Apr 2015
Can you be more specific about your question? What is this data? What do you mean by "smooth envelope"? What is the specific goal?

Accedi per commentare.

Risposta accettata

John D'Errico
John D'Errico il 21 Apr 2015
Modificato: John D'Errico il 21 Apr 2015
The problem is, you don't really want an envelope.
For example, here are a couple of fits that will produce an envelope.
slm_upper = slmengine(x,y,'env','sup','plot','on','knots',30);
slm_lower = slmengine(x,y,'env','inf','plot','on','knots',30);
Those are envelope fits, i.e., least upper bound and greatest lower bound functions.
But what you have drawn are functions that sort of look like that, but go where you want them to go, ignoring some of your data. So they skip some points that you consider outliers. You want maybe a function that can intelligently (defined by what you consider an outlier) exclude perhaps some 1 to 5% of the points as outliers.
The problem is, the eye is good at seeing a pattern that it likes. The computer, not so good. Computers do what they are programmed to do.
Perhaps the best suggestion I can offer is to use a tool like my SLM as below in a multiple step process:
slm_upper0 = slmengine(x,y,'env','sup','plot','on','knots',30);
tol= max(y)*1.e-14;
res_upper = slmeval(x,slm_upper,0) - y;
keep_upper = find(res_upper > tol);
drop_upper = find(res_upper <= tol);
slm_upper = slmengine(x(keep_upper),y(keep_upper),'env','sup','plot','on','knots',30);
hold on
plot(x(drop_upper),y(drop_upper),'ro')
Thus, find the points that were on the boundary in one envelope, then exclude them form the fit, and repeat the fit. Do a similar procedure for a lower semi-envelope. I'm not sure I see a better way.
The SLM toolbox is on the file exchange.
  1 Commento
Si
Si il 21 Apr 2015
Thanks for your answer very helpful indeed

Accedi per commentare.

Più risposte (1)

Youssef  Khmou
Youssef Khmou il 21 Apr 2015
Modificato: Youssef Khmou il 21 Apr 2015
try the following basic solution using Hilbert transform :
fs=40;
t=0:1/fs:4-1/fs;
f=15;
y=1.5*sin(2*pi*f*t).*exp(-1.1*t);
y=y+0.1*randn(size(t));
plot(t,y)
hold on;
z=abs(hilbert(y));
plot(t,smooth(z,0.25),'r');
  2 Commenti
Si
Si il 21 Apr 2015
Thanks for your answer - much appreciated.
Hany Ferdinando
Hany Ferdinando il 29 Gen 2019
Hi Youssef,
I also faced the same problem using envelop function. However, using your approach seemed not useful for me. The blue line is the PPG signal. The envelope calculation using hilbert seemed not what I expected. What do you think?
Thanks

Accedi per commentare.

Tag

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by