# Do the Inverse Fourier transform from frequency distribution

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dang khoa tran on 11 Feb 2020
Commented: dang khoa tran on 11 Feb 2020
Hello everyone.
I have a set of data : "y_spectrum" shows the electric field amplitude and "t_spectrum" shows the time.
I have done the Fourier transform of those data to get the frequency component according this code:
Ts = mean(diff(t));
Fs = 1/Ts;
Tstd = std(diff(t));
Fs = 12E+15; % Sampling Frequency
[Er,tr] = resample(E,t,Fs); % Resample To Regularly-Spaced Intervals
figure
plot(t,E,'.b')
hold on
plot(tr,Er,'-r')
hold off
grid
legend('Original E', 'Resampled E')
Fn = Fs/2; % Nyquist Frequency
L = numel(tr); % Vector Lengths
Erm = Er - mean(Er);
FT_Erm = fft(Er)/L;
Fv = linspace(0, 1, fix(L/2)+1)*Fn;
Iv = 1:numel(Fv);
[pks,locs] = findpeaks(abs(FT_Erm(Iv))*2, 'MinPeakHeight',3E+10);
figure
plot(Fv, abs(FT_Erm(Iv))*2)
hold on
plot(Fv(locs), pks, '.r')
hold off
text(1.5E+15, 7.5E+10, sprintf('Peak %10.3E Frequency %10.3E\n', [pks Fv(locs).'].'))
Is there anyway to do the inverse Fourier transform of the frequency domain obtained from above code?
Thank you very much

KALYAN ACHARJYA on 11 Feb 2020
Is it?
ifft(FT_Erm)

#### 1 Comment

dang khoa tran on 11 Feb 2020
I also try this but I think it is not since it still shows the variation in frequency domain.