# APPENDIX C compwind.m

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## compwind.m

% % FUNCTION compwind %

% Display the sound before windowing and after windowing % function r = compwind(s, fs) l = length(s); m = 100; n = 256; nbFrame = floor((l - n) / m ) + 1; %

% Create a matrix M containg all the frames % for i = 1:n for j = 1:nbFrame M(i, j) = s(((j - 1) * m) + i); end end %

% Matrix M created. Now apply HAMMING window and store in matrix N. Column vectors of N are

% the original frame vectors transformed by the Hamming window filter %

h = hamming(n); N = diag(h) * M;

%

% Now plot the window, without window, and with window %

%

% Plot the Hamming window %

t = (0:n-1); subplot(3,1,1); plot(t,h);

title('Hamming Window'); xlabel('Samples');

ylabel('Amplitude'); %

% Plot the sound without windowing %

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126 subplot(3,1,2);

plot(t,M);

title('Sound frames before windowing'); xlabel('Samples');

ylabel('Amplitude'); %

% Plot the sound with windowing %

subplot(3,1,3); plot(t,N);

title('Sound frames after windowing'); xlabel('Samples');

ylabel('Amplitude'); r=1;

% Plot the Hamming window %

t = (0:n-1); subplot(3,1,1); plot(t,h);

title('Hamming Window'); xlabel('Samples');

ylabel('Amplitude'); %

% Plot the sound without windowing %

subplot(3,1,2); plot(t,M);

title('Sound frames before windowing'); xlabel('Samples');

ylabel('Amplitude'); %

% Plot the sound with windowing %

subplot(3,1,3); plot(t,N);

title('Sound frames after windowing'); xlabel('Samples');

ylabel('Amplitude'); r=1;

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