MATLAB: Is there a bandwidth limit on the bandstop filter

filter

I have the following code which is stopping a super narrow band on a signal. It runs but won't complete and locks up matlab. I assume becasue I'm pushing the filter past it's limit. Can anyone confirm this?

y = bandstop(signal, [4500 950000], 5e9);

Thanks

Best Answer

The easiest way to see what’s going on with it is to use fvtool to look at it, and to give it a short random signal to look at the output:

signal = rand(1, 1E+4);
[y,df] = bandstop(signal, [4500 950000], 5e9);
fvtool(df)
figure
plot(y)

It appears to be a well-designed filter, and works with a random signal. I suspect that something about your ‘signal’ vector could be part of the problem, possibly its amplitude, since the output of the random signal (with an amplitude between 0 and 1) produces an output on the order of

. The normalised frequency of the stopband center frequency is about

. (In my experience, this is a bit extreme.)

In situations like this, it’s sometimes worthwhile to design both a lowpass filter and a highpass filter, and then add the output vectors. (There is no way to cascade them, since the output of one filter will not overlap with the output of the other filter.)

The problem does not appear to be with the filter itself, since the fvtool analysis suggests that it’s stable and works well.

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Eliminating the d-c (or constant) offset by subtracting the mean is a good first step. The detrend function is definitely useful, but not always appropriate for signal processing, and probably not at all for your application. It will not eliminate low-frequency periodic baseline variations. For that, you need a highpass (or better, bandpass) filter. A highpass filter will eliminate the low-frequency baseline variation. A bandpass filter will also eliminate any high frequency noise.

A prototype FIR bandpass filter design (using kaiserord and fir1) is here:

Fs = 44100;                                                     % Sampling frequency
fcuts = [10 20 20E+3 21E+3];                                    % Frequency Vector (Frequencies in Hz) For All Passbands And Stopbands
mags =   [0 1 0];                                               % Magnitude (Defines Passbands & Stopbands)
devs = [0.05  0.01  0.05];                                      % Allowable Deviations
[n,Wn,beta,ftype] = kaiserord(fcuts,mags,devs,Fs);
n = n + rem(n,2);
hh = fir1(n,Wn,ftype,kaiser(n+1,beta),'scale');
figure(1)
freqz(hh, 1, 2^14, Fs)

Change the frequencies in ‘fcuts’ and sampling frequency (‘Fs’) to be appropriate to your signal. See the documentation for kaiserord (link) for details.

I also suggest that you use the code between the first (top) two plot figures in the fft (link) function. That will help you plot and understand your original and plotted signals.

Best Answer

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