lab 3 - 1.1 Fs=10 f=1; t=[0:1] x=cos(2*pi*f*t);...

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1.1 Fs=10 f=1; t=[0:1] x=cos(2*pi*f*t); xd=x[1:L:end]); %The purpose of downsampling is to decrease the sampling rate. This is done %by takeing the original sampling rate and dividing it by factor L; this %becomes the rate of the downsampled signal. Therefore, the downsampled %signal has a sampling rate of the original sampling rate divided by L, or %1/L. 1.2 function [X,freq]=positiveFFT(x,Fs) N=length(x); %get the number of points k=0:N-1; %create a vector from 0 to N-1 T=N/Fs; %get the frequency interval freq=k/T; %create the frequency range X=fft(x)/N; % normalize the data end Fs =10; n=[0:10]; y=cos(2*pi*1*n/Fs); [YfreqDomain,frequencyRange] = positiveFFT(y,Fs); stem(abs(frequencyRange),abs(YfreqDomain)); xlabel( 'Freq (kHz)' ) ylabel( 'Amplitude' ) title( 'Part 1.2' ) 1.3
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Fs=10000; L=8; n=[0:10000]; x=cos(2*pi*1000*n/Fs); y=x(1:L:end); [YfreqDomain,frequencyRange] = positiveFFT(y,Fs/L); stem(abs(frequencyRange),abs(YfreqDomain)); xlabel( 'Freq (Hz)' ) ylabel( 'Amplitude' ) title( 'L=8' ) 1.5 y = imread( 'barbaraLarge.gif' ); %read the signal y from the image file L = 2; %define the downsampling factor [rows,columns] = size(y); %get the number of rows and columns in the image;
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yd = zeros(floor(rows/L),floor(columns/L)); %Find the new signal yd that is downsampled by factor L for i=1:floor(rows/L), for j=1:floor(columns/L), %select one sample from each 2row&2column block yd(i,j) = y((i-1)*L+1, (j-1)*L+1); %insert this sample in yd end end %configure the output image(below) figure( 'Position' ,[100 100 size(y,2) size(y,1)], ... 'MenuBar'
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lab 3 - 1.1 Fs=10 f=1; t=[0:1] x=cos(2*pi*f*t);...

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