My computer won't run a code with bandpass filter

Hi everyone, I'm having trouble running a code that involves passing a signal through a bandpass filter. The exact same code runs on someone else's computer, so we are not sure why it won't run properly on mine. Here is the code.

%-1.599 bias

clc;

close all;

clear all;

Fs = 125e3; % Sample Frequency in Hz

fnyquist = Fs/2; %nyquist frequency

signal_with_bias = csvread('BallSignal.csv',1,0);

sig_i = signal_with_bias(:,1); %in_phase signal

sig_i = sig_i - mean(sig_i); %remove bias

sig_q = signal_with_bias(:,2);%quad_signal

sig_q = sig_q - mean(sig_q); %remove bias

signal = complex(sig_i, sig_q); %the complex signal

%Calculate DC bias

bias_i = mean(signal_with_bias(:,1));

fprintf('%f\n', bias_i)

bias_q = mean(signal_with_bias(:,2));

fprintf('%f\n', bias_q)

N =length(signal); %length of signal

t = (0:1:N-1)/Fs; %time period

Ts = mean(diff(t)); %sampling Time

fs =(0:N-1).*(Fs/N); %frequency vector

Is = 1:length(fs); % Index Vector

w = hann(N); %hanning window

ff=fft((signal .*w)); %fourier transform of the signal after hanning window

power = abs(ff).^2/N;

%b_signal = bandpass(ff, [2.35e4, 2.45e4],Fs); % apply a bandpass filter 23500Hz to 24500Hz

b_signal = bandpass(signal, [2.399e4, 2.405e4],Fs); % apply a bandpass filter 23500Hz to 41000Hz

fff =fft(b_signal.*w);

b_power = abs(fff).^2/N;

sig_f = ifft(fff); % inverse fourier transform of the filtered signal

%Plot Complex Signal

figure(1)

plot(t,real(signal .*w),'r',t,imag(signal .*w),'k');

title('Signal'); xlabel('time(s)'); ylabel('Voltage(V)');

legend('real', 'imaginary');

%Plot the Power Spectrum

figure(2)

plot(fs, power); %Frequency Vs. Power

title('Power Spectrum'); xlabel('Frequency(Hz)'); ylabel('Magnitude');

norm_ff = fft(signal)/N;

amp_fts = abs(norm_ff(Is))*2; % Spectrum Amplitude

phs_fts = angle(norm_ff(Is)); % Spectrum Phase

phase=atan2(imag(signal),real(signal))*180/pi; %phase information

%Power Spectrum after bandpass filter

figure(3)

plot(fs, b_power);

title('Power Spectrum of bandpass signal'); xlabel('Frequency(Hz)'); ylabel('Magnitude');

xlim([0,8e4]);

%Plot Bandpass Signal

figure(4)

plot(t,real(sig_f), 'r', t, imag(sig_f), 'k'); % plot the real and imaginary bandpass signal

title('Bandpass signal'); xlabel('time(s)'); ylabel('Voltage');

legend('real', 'imaginary');

I've attached the error I get. I tried running another code from mathworks' website and got a similar error. I have the signal processing toolbox and other codes using the toolbox work properly as long as a bandpass filter is not used. Is there something else I need to download? Any help is much appreciated.

[Star Strider]

What MATLAB version/release do you have?

What MATLAB version/release does someone else’s computer have?

The bandpass function was introduced in R2018a.

Bandpass (and other) filters are relatively straightforward to design using command line functions.

[Michele Woodland]

We both have R2020a.

[Star Strider]

I don’t have ‘BallSignal.csv’ so I can’t run your code to see if I can figure out if the problem may have something to do with that file (although I doubt it’s the problem).

When I substitute:

signal_with_bias = [linspace(0, 1, 100).', rand(100, 1)+10];

(asssuming the the first column is supposed to be time and the second the signal), without any other changes, the code runs correctlly with no errors. The narrowband bandpass filter also appears to work correctly.

It might be best for you to use the Contact Us telephone handset icon in the upper-right corenr of this page to request Technical Support. Include the URL of this thread so you don’t have to repeat everything, and so Technical Support knows what you’ve already tried.

[Michele Woodland]

I've attached the file (I changed the file to BackandForthMovement). The two columns are actually the in-phase and quadrature data. I will do that, thank you.

[Mathieu NOE]

hello

late input from me

just in case it might help you in the future, this code is about the standard digital filters used in audio

maybe sometimes the good old fashioned way can help