Applied to functions of continuous arguments, Fourier-related transforms include:
For usage on computers, number theory and algebra, discrete arguments (e.g. functions of a series of discrete samples) are often more appropriate, and are handled by the transforms (analogous to the continuous cases above):
The use of all of these transforms is greatly facilitated by the existence of efficient algorithms based on a fast Fourier transform (FFT). The Nyquist–Shannon sampling theorem is critical for understanding the output of such discrete transforms.
The Fourier series represents ∑ n = − ∞ ∞ f ( n T ) ⋅ δ ( t − n T ) , {\displaystyle \scriptstyle \sum _{n=-\infty }^{\infty }f(nT)\cdot \delta (t-nT),} where T is the interval between samples. ↩