hello
I did quite a few modifications / simplifications
there are several variables that seem to never be used , so I commented them
at the end there is only one single variable that drives how many filters are considered : numFilts
I supposed that you wanted to have all filter bode plots overlaid, so that's the first major modification (see 1st loop )
the second loop is simply based on the results obtained in the first loop , here also I had to modify the time vector and signal definition so it's frequency is clearly defined (and you can make it match (or not) one of the BP filter central frequency)
%% parameters
fs = 20e3; % 16e3 is not enough if you need to see the effect of a bandpass filter with a center frequency at 8000 Hz
numFilts = 5;
% filter_number = 10;
%range = [50 8000];
BW = 100; % filter bandwith
CentralFreq = linspace(1000, 8000, numFilts);
CF1=CentralFreq -BW/2;
CF2=CentralFreq +BW/2;
%% plots
figure(1)
hold on
for ii = 1:numel(CentralFreq)
bpfilt{ii} = designfilt( ...
'bandpassfir', ...
'FilterOrder',20, ...
'CutoffFrequency1',CF1(ii), ...
'CutoffFrequency2',CF2(ii), ...
'SampleRate',fs);
[h{ii},f] = freqz(bpfilt{ii}.Coefficients,1,1024,fs);
subplot(211)
plot(f,db(abs([h{:}])));
title('Magnitude')
ylabel('Magnitude (dB)')
xlabel('Frequency (Hz)')
subplot(212);
plot(f,180/pi*(angle([h{:}])));
title('Phase')
ylabel('Phase (degrees)')
xlabel('Frequency (Hz)')
end
hold off
% impulse_input = 0*fs;
% impulse_input(1) = 1;
%%
% Reference signal with some white noise to benchmarch the created filter performances
% t = linspace(0,2*pi,200);
rng(13) % Make it repeatable
dt = 1/fs;
samples = 200;
freq = 4500; % signal frequency in Hz
t = (0:samples-1)*dt; % time vector according to sampling frequency fs; maybe you want to increase the number of samples
x = sin(2*pi*freq*t) + 0.25*rand(size(t)); % Ref Signal with a noise
% Simulation of 1-D digital filter: x_filtered = filter(b, a, x);
a = 1;
figure(2)
hold on
CoLoR = rand(numFilts, 3);
for ii = 1:numFilts %THIS ONE!!!
[x_filtered(ii,:),zf(:,ii)]=filter(bpfilt{1, ii}.Coefficients, a, x);
plot(t,x_filtered(ii,:), 'LineWidth', 1.25, 'Color', CoLoR(ii,:))
LEGs{ii} = ['Filter # ' num2str(ii)];
legend(LEGs{:})
end
plot(t, x, 'k-', 'LineWidth', 2, 'DisplayName', 'Data')
xlabel('t')
ylabel('x(t) & x_{filtered} (t)')
grid on
legend('Show')
fprintf('Number of generated filters: %d \n', numFilts)
