Iam tying to run the following code on the data,
but it gives me an error:
Error using .* Matrix dimensions must agree.. The error occurs here: xw=x .* xh'; % Window the signal.
Can someone help me?
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DataTbl=readtable('6largeabsorbers100 pointds44.545 msweep2.csv');
[Ro,Co]=size(DataTbl);
Data=table2array(DataTbl);
Frequency=Data(:,1);
S21Mag=Data(:,2);
S21Ang=Data(:,3);
%%% DAta Preperation %%%%%%
[Re,Im]=pol2cart(S21Ang,S21Mag);
CmpLx=complex(Re,Im);
ampitude=sqrt((Re .^2)+(Im .^2)); % amplitude value
ampitudedB= 20*log10(ampitude)+10; % amplitude in dB
plot (Frequency,ampitudedB, 'k'); %Amplitudein db verus time
xlabel('Frequency [Hz]') % x-axis label
ylabel('H(t0,f) [dB]') % y-axis label
title('suburban-6 small absorbers- Time-invariant transfer function')
%--FFT on data
f1=2420000000; % Signal frequency
MD=10; % measurement duration in se
FS=length(data)/MD; % sampling frequency in Hz
N=256; % Number of samples
N1=1024; % Number of FFT points
n=0:N-1; % Index n
f=(0:N1-1)*FS/N1; % Defining the frequency points [axis]
x= ampitudedB/FS;
XR=abs(fft(x,N1)); % find the magnitude of the FFT using No
% windowing (i.e. Rectangular window)
xh=hamming(N); % Define the hamming samples
xw=x .* xh'; % Window the signal
XH=abs(fft(xw,N1)); % find the magnitude of the FFT of the
% windowed signal.
subplot(2,1,1); % Start plotting the signal
plot(f(1:N1/2),20*log10(XR(1:N1/2)/max(XR)));
title('Spectrum of x(t) using Rectangular Windows');
grid;
xlabel('Frequency, Hz');
ylabel('Normalised Magnitude, [dB]');
subplot(2,1,2);
plot(f(1:N1/2),20*log10(XH(1:N1/2)/max(XH)));
title('Spectrum of x(t) using Hamming Windows');
grid;
xlabel('Frequency, Hz');
ylabel('Normalised Magnitude, [dB]');
%---------------------
x and xh' must have the same dimensions unless one of both is a scalar
".*" is an element-by-element multiplication so you must have two vectors with the same number of elements.
You should therefore check size(x) and size(xh'). Make sure you get the same size. Otherwise, you need to compute the hamming window with the exact number of samples as your x.
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