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Echo and Noise cancellation in MATLAB

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Arslan Khan
Arslan Khan 2021-4-16
编辑： Arslan Khan 2021-4-16
Hi Experts!
I have a project about Echo cancelling Project and I have done some coding for designing the filters for echo cancellation. I couldn't get any help from internet.
The project says as :
The received_signal is professor's voice with noise and echo while Test Signals are just signals for sent and received.
And i have developed the following code.
Echo Canceling Project
1. Load the .mat file (serial number 33)
clear all; clc;
data=load("F33.mat");
2.Play the sound ,received_signal
%sound(data.Received_Signal,data.Fs)
% the sound was of professor with noise and echo
3. Using Test Signal , find Impulse Response.
y(n)= Received_Test_Signal
x(n)= Test_Signal
h(n)=x(n)∗y(n)
hn=conv(data.Received_Test_Signal,data.Test_Signal,"full");
plot(impz(hn));
title('Impulse Response of Test Signals');
Values of coefficients ai and 5001 x 1 of x(n) means it will have value of n1 to n5001.
[a]=(data.Test_Signal);
4.Recover the signal x(n)
% Using the Approach of LMS for finding the filter
d=100;
x = data.Test_Signal(d+1:end) ;% desired echo-free signal
y = data.Received_Signal(d+1:end) + 0.4*data.Received_Signal(1:end-d) ;% signal with echo
% Using LMS
M = 3*d;% FIR filter length
delta = 0.0001 ;% LMS step size
hzf = zeros(M,1);% Initial filter IR values
ev = [];
for i=M+1:length(x)
xn = x(i);% desired sample value
yn = y(i-M+1:i);
xnhat = hzf'*yn ;% filter output value
en = xn - xnhat ;% current error
hzf = hzf + delta*yn*en; % update
% Plotting
ev = [ev abs(en)];
if rem(i,100)==0 ;% too slow to plot every iteration
subplot(2,1,1);
plot(hzf);
title('Impulse response');
subplot(2,1,2);
plot(ev) ;
title('|error|');
pause(0.001);
end
end
% filtering
xn_=conv(data.Received_Signal,hzf)
z=filter(hzf,1,data.Received_Signal)
5. The zplane , for order and stability
figure(2)
zplane(hzf)
n=filtord(hzf)
% stable
isstable(hzf)
6. Structure for filter
% the filter is an IIR filter given by
figure(2)
plot(hzf)
7. IIR to FIR filter
% We have to use Window method to limit the infinite Impulse Response of
% the inverse filter. i.e hamming window method
windw=[ones(1,100)]
FIR_approx=hzf.*windw
plot(FIR_approx)
8. Applying to y(n) to remove echo
ec_removed=filter(1,FIR_approx(:),data.Received_Signal)
sound(ec_removed)
9. Plot the Recovered signal against Frequency
plot(fft2(data.Received_Signal))
xlabel('-----Frequency(Hz)--->');
10. Using fdatool , Remove noise from x(n). Serial Number =33, Using Chebyshev 1 with order 34
%recov=filter(1,FilterDesign,data.Received_Signal)
%sound(recov)

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