# Fourier transform in continuous time signal

Version 1.0.0 (273 KB) by
The project aims to demonstrate the importance and functionality of Fourier transform in analyzing continuous-time signals.
Updated 26 Apr 2024

The project scope includes demonstrating Fourier transform's application in analyzing continuous-time signals. It covers concepts like frequency spectrum, amplitude, and phase. However, it may not delve deeply into advanced topics or specific applications beyond the basics. The focus is on providing a clear and intuitive demonstration of Fourier transform's significance and functionality.
% Define the continuous-time signal
t = -5:0.01:5; % Time vector
x = sin(2*pi*t) + 0.5*cos(4*pi*t); % Example signal
% Compute the Fourier transform
X = fftshift(fft(x));
% Frequency vector
Fs = 1/(t(2)-t(1)); % Sampling frequency
f = linspace(-Fs/2, Fs/2, length(t));
% Plot the original signal
subplot(2,1,1);
plot(t, x);
xlabel('Time (s)');
ylabel('Amplitude');
title('Original Signal');
% Plot the magnitude of the Fourier transform
subplot(2,1,2);
plot(f, abs(X));
xlabel('Frequency (Hz)');
ylabel('Magnitude');
title('Fourier Transform');
% Adjusting plot limits for better visualization
xlim([-10, 10]); % Set the frequency range to display

### Cite As

Jeganathan (2024). Fourier transform in continuous time signal (https://www.mathworks.com/matlabcentral/fileexchange/164526-fourier-transform-in-continuous-time-signal), MATLAB Central File Exchange. Retrieved .

##### MATLAB Release Compatibility
Created with R2024a
Compatible with any release
##### Platform Compatibility
Windows macOS Linux