# What information does fourier transform carry? [duplicate]

As one starts learning signal processing, then comes inevitably the topic of Fourier Transforms. Unfortunately I have difficulties not in computing but in interpreting the results of the Fourier Transforms, in particular the one being Continuous-Time Fourier Transform, CTFT, of the signal $x(t)$ which is: $$X(j\omega) = \int_{-\infty}^{\infty}{x(t)e^{-j\omega t}dt}$$

Now I wonder what kind of information does this $X(j\omega)$ give about the signal $x(t)$? An example is highly appreciated, if possible.

## marked as duplicate by Marcus Müller, Laurent Duval, MBaz, jojek♦, Peter K.♦Feb 15 '16 at 12:59

There are a variety of Fourier Transforms (and Series) such as Continuous Time FT, Discrete Time FT, Discrete FT all of which are generally attributed to the fundamental assertion made by J.B.Fourier about at the beginning of 19th century, which claims (without proof) that "if a continuous-time signal (function) x(t) is periodic with T, then it is possible to represent that signal x(t) as an infinite sum of harmonically related trigonometric functions (sines and cosines) as $x(t)= \sum{ a_k \sin { 2\pi kt \over T} + b_k \cos { 2\pi kt \over T}}$ in which the weights $a_k$ and $b_k$ (the Fourier Coefficients) represent the amount of that particular harmonic in the signal x(t) being analysed"
In fact the above argumentation is strictly for Continuous-Time Fourier Series. But the core idea is generalised into Fourier-Transforms of aperiodic and periodic (with the help of impulse $\delta (t)$ functions) signals. There are conditions on which signals can have such a representation.
In essence, computing a Fourier Transform means finding those coefficients $a_k$ and $b_k$ for which the method is suggested by the analysis equation of the Fourier transform, while the equality in the first paragraph is noted as the synthesis equation.