Notch Filter

code3.m

close all;
clear all;

load('noisy_ECG_sig.mat')
y=noisy_ECG_sig; %the signal loaded
L=length(y)
sampling_freq = 1000


figure; % plot the original signal
plot([1:2570],y);
title('Original ECG Signal')

% Question 2) plot the frequency response of both the original signal(noisy_ECG_sig) and the filtered signal Yn

%% plot frequency response of the original signal %% 
NFFT=2^nextpow2(L);
f = sampling_freq/2*linspace(0,1,NFFT/2+1);
Y=fft(y,NFFT)/L;
figure, plot(f,2*abs(Y(1:NFFT/2+1)));
title('frequency response of the original signal');
ylabel('amplitude');
xlabel('frequency');
%%  %% 


num=[0.9955 -1.8936 0.9955];
den=[1 -1.8936 0.9911];
filtered_y = filter(num,den,y);

%% plot frequency response of the filtered signal %% 
NFFT=2^nextpow2(L);
f = sampling_freq/2*linspace(0,1,NFFT/2+1);
f_Y=fft(filtered_y,NFFT)/L;
figure, plot(f,2*abs(f_Y(1:NFFT/2+1)));
title('frequency response of the filtered signal');
ylabel('amplitude');
xlabel('frequency');
%% %%


figure;
plot([1:2570],filtered_y); % plot the filtered signal
title('Filtered ECG Signal')

% Question 3) By observing the distinct changes in the frequency components
% in the above frequency plots, predict the nature of the filter

fvtool(num,den) 

%q4) verify your results using 'fvtool' matlab function

Where is .mat file? In your blog it is not downloadable and not even able to save this .mat file.

Hey, apologies for the broken link.
I uploaded it now, https://blog.ramith.fyi/static/math_embed/noisy_ECG_sig.mat

Thanks