How do I fix this code with some protting and defining errors?

I have a project but I'm not sure what's wrong really with the code that I have. Section 1 through 5 seem good (but if you see anything glaringly wrong please feel free to tell me but my problem isn't for those sections. Section 6 just isn't seeming to run well and I am sick of looking at this code so i just need other eyes on it pls.

The prompt for section 6 is: "Design a filter using window-based filter design to selectively remove the noise. Use the built-in function fir1. Apply the filter to each signal while experimenting with different cutoff frequencies. Plot the selected filter impulse response and each of the filtered signals. What kind of filter was selected and what were the cutoff frequencies?"

The code is:

%{

Signals and Systems

Project 3

Names

%}

close all; clear; clc

% Part 1 - plot magnitude spectrum of x(t) over [0,w] =====================

% Variables and equations

w = 0:(pi/1000):pi;

Xw = (-j./w) .* (1 - exp(-100j.*w));

% Plot magnitude spectra

figure

plot(w, abs(Xw))

xlabel('Frequency ω'); ylabel('|X(ω)|'); title('Magnitude Spectrum of X(ω)')

% Part 2 - FFT plot =======================================================

% Variables and equations

Ts=1; t=0:Ts:100; N = 1024;

xtn = heaviside(t) - heaviside(t-100);

DFT1 = fft(xtn, N);

wTs = linspace(0,2*pi,N);

% Plot DFT magnitude spectrum

figure

plot(wTs, abs(DFT1))

xlabel('ωTs'); ylabel('|X(ω)|'); title('DFT Magnitude Spectrum')

axis('tight')

% Part 3 - FFT plot for different N =======================================

% N=64

N=64;

wTs = linspace(0,2*pi,N);

DFT2 = fft(xtn, N);

% Subplot for N=64

figure

sgtitle('DFT Magnitude Spectra for Different N')

subplot(3,1,1)

plot(wTs, abs(DFT2));

xlabel('ωTs'); ylabel('|X(ω)|'); title('N=64')

axis('tight')

% N=128

N=128;

wTs = linspace(0,2*pi,N);

DFT3 = fft(xtn, N);

% Subplot for N=128

subplot(3,1,2)

plot(wTs, abs(DFT3));

xlabel('ωTs'); ylabel('|X(ω)|'); title('N=128')

axis('tight')

% N=512

N=512;

wTs = linspace(0,2*pi,N);

DFT4 = fft(xtn, N);

% Subplot for N=64

subplot(3,1,3)

plot(wTs, abs(DFT4));

xlabel('ωTs'); ylabel('|X(ω)|'); title('N=512')

axis('tight')

% Part 4 - Phase and magnitude spectra of clean AP signal =================

% Data, variables, equations

apdata = load('apdata.mat');

Ts=0.0796; ws=1/(2*Ts);

fftC = fft(apdata.clean(:,1));

magC = abs(fftC); phaseC = angle(fftC);

wTsC = linspace(0, ws, length(magC));

figure

sgtitle('DFT Spectra for Clean Action Potential')

subplot(2,1,1)

plot(wTsC, magC)

xlabel('ωTs'); ylabel('|X(ω)|'); title('Magnitude Spectrum')

xlim([0,ws])

subplot(2,1,2)

plot(wTsC, phaseC)

xlabel('ωTs'); ylabel('<X(ω)'); title('Phase Spectrum')

xlim([0,ws])

% Part 5 - Phase and magnitude spectra of noisy AP signal =================

% Data, variables, equations

fftN = fft(apdata.noisy(:,1));

magN = abs(fftN); phaseN = angle(fftN);

wTsN = linspace(0, ws, length(magN));

figure

sgtitle('DFT Spectra for Noisy Action Potential')

subplot(2,1,1)

plot(wTsN, magN)

xlabel('ωTs'); ylabel('|X(ω)|'); title('Magnitude Spectrum')

xlim([0,ws])

subplot(2,1,2)

plot(wTsN, phaseN)

xlabel('ωTs'); ylabel('<X(ω)'); title('Phase Spectrum')

xlim([0,ws])

% Part 6 - Filter design ============ THIS IS THE PART I NEED HELP WITH PLS

cutoff_frequencies = [30, 5, 15, 50]; % Cutoff frequencies to test

filtered_signals = cell(length(cutoff_frequencies), 1); % Cell array to store filtered signals

for i = 1:length(cutoff_frequencies)

% Design filter

cutoff = cutoff_frequencies(i)/125; % Normalize cutoff frequency

b = fir1(50, [1/125 cutoff]);

%Plotting the impulse response

figure;

stem(b, 'filled');

xlabel('Sample Index');

ylabel('h[n]');

title('Impulse Response of the Filter');

% Apply filter to noisy signal

filtered_signals{i} = filter(b, 1, apdata.noisy(:,1));

% Plot filtered signal and compare with clean signal

figure;

plot(wTsC, magC, '-r', 'DisplayName', 'Clean'); % Plot the clean signal

hold on;

plot(wTsN, magN, '-k', 'DisplayName', 'Noisy'); % Plot the noisy signal

plot(wTsN, abs(filtered_signals{i}), '-b', wTsN,(apdata.noisy(:,1)), '-r');

title(sprintf('Filtered Signal (cutoff = %d Hz)',cuttoff_frequencies(i)));

end

% Plotting the filtered signals

figure(7)

subplot(4,1,1)

plot(wTsN, abs(filtdirty1))

xlabel('w')

ylabel('|X(w)|')

title('Filtered Signal - Cutoff = 30Hz')

subplot(4,1,2)

plot(wTsN, abs(filtdirty2))

xlabel('w')

ylabel('|X(w)|')

title('Filtered Signal - Cutoff = 5Hz')

subplot(4,1,3)

plot(wTsN, abs(filtdirty3))

xlabel('w')

ylabel('|X(w)|')

title('Filtered Signal - Cutoff = 15Hz')

subplot(4,1,4)

plot(wTsN, abs(filtdirty4))

xlabel('w')

ylabel('|X(w)|')

title('Filtered Signal - Cutoff = 50Hz')

% Plotting the impulse response of the filters

figure(8)

subplot(4,1,1)

impz(b1)

title('Impulse Response of Filter - Cutoff = 30Hz')

subplot(4,1,2)

impz(b2)

title('Impulse Response of Filter - Cutoff = 5Hz')

subplot(4,1,3)

impz(b3)

title('Impulse Response of Filter - Cutoff = 15Hz')

subplot(4,1,4)

impz(b4)

title('Impulse Response of Filter - Cutoff = 50Hz')

[Luca Ferro]

could you share the file apdata.mat?

and what do you mean with ' isn't seeming to run well'?