Hi everyone,
I predicted a signal using mathematical model and I want to compare it with a sensor signal. The problem is my predicted signal reaches the maximum value within fraction of milli seconds. So, I want to include the response time of the sensor in the mathematical model and correct the predicted signal. I tried first order low pass filter using lowpass command in Matlab, but I didn't find any difference. The frequency response(FFT) of my predicted signal shows that my signal always lies below -10dB. Is there any way to include the information about the rise time of the sensor and smoothen the signal?
Thanks!!!
tr = 1.2; %response time
t_s = 0.2; % sampling rate in seconds
f_pass = 0.35/(tr);
f_s = 1/t_s;
Ysim_pt = lowpass(Ysim,f_pass,f_s);

 採用された回答

Andrey Kiselnikov
Andrey Kiselnikov 2019 年 8 月 19 日

0 投票

If you do not see any changes after filtering it means that all signal components pass through your filter. To visualize it and compare filter response and signal spectrum (use FFT for it) add this string in your script, may bee it can help you.
d = fdesign.lowpass('Fp,Fst,Ap,Ast',f_pass,f_stop,1,60);
Hd = design(d);
fvtool(Hd);
values "1, 60" are defaluts for "lowpass" command.

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