One of the benefits of using the Fourier transform of a function is that convolutions become multiplications. This is important when solving a differential equation with its Green's function. If the Green's function comes from a differential operator $D^*D$, where $D$ is a differential operator and $D^*$ is its adjunct, then the Green's function is not singular at the origin, and is continuous. It expands a function space called a reproducing kernel hilbert space, RKHS, and all functions in this space can be written as linear combinations of the Green's function evaluated on one argument, and the solution to the differential equation $D^*D u = y$ would be of that form. OK, don't digrees anymore... to the cheese...

In the Fourier domain we operate on frequencies $\omega$. For example, to attenuate the noise, we decrease the power in the high omegas, which accounts for a convolution (with a Gaussian, for example). If we see this linear operation as a matrix, the convolution operator that has one (let's say) dimensional Gaussians in its rows (in the time/space domain) becomes a diagonal in the Fourier domain.

The page popped up with much to follow on. In particular, I liked this paragraph

In MatlabThe moral of the story is that the Fourier Transform may be thought of as a change of basis. The Fourier integral projects a function onto the basis functions of a new coordinate system whose basis functions are the complex exponentials. In this new basis, the convolution operator is diagonal and everything is simple. The convolution operator acts on each Fourier component independently by multiplying the component by an associated magnitude and phase.

C=[4 1 2 3; 3 4 1 2; 2 3 4 1; 1 2 3 4]

C =

4 1 2 3

3 4 1 2

2 3 4 1

1 2 3 4F=fft(C)

F =

10.0000 10.0000 10.0000 10.0000

2.0000 - 2.0000i -2.0000 - 2.0000i -2.0000 + 2.0000i 2.0000 + 2.0000i

2.0000 -2.0000 2.0000 -2.0000

2.0000 + 2.0000i -2.0000 + 2.0000i -2.0000 - 2.0000i 2.0000 - 2.0000i

F*C*F'

ans =

1.0e+003 *

4.0000 0 0 0

0 0.0640 - 0.0640i 0 0

0 0 0.0320 0

0 0 0 0.0640 + 0.0640i