A given function or signal can be converted between the time and frequency domains with a pair of mathematical operators called transforms. An example is the Fourier transform, which converts the time function into a sum or integral of sine waves of different frequencies, each of which represents a frequency component. The 'spectrum' of frequency components is the frequency-domain representation of the signal. The inverse Fourier transform converts the frequency-domain function back to the time function. A spectrum analyzer is the tool commonly used to visualize real-world signals in the frequency domain.

Some specialized signal processing techniques use transforms that result in a joint time–frequency domain, with the instantaneous frequency being a key link between the time domain and the frequency domain.

In using the Laplace, Z-, or Fourier transforms, a signal is described by a complex function of frequency: the component of the signal at any given frequency is given by a complex number. The magnitude of the number is the amplitude of that component, and the angle is the relative phase of the wave. For example, using the Fourier transform, a sound wave, such as human speech, can be broken down into its component tones of different frequencies, each represented by a sine wave of a different amplitude and phase. The response of a system, as a function of frequency, can also be described by a complex function. In many applications, phase information is not important. By discarding the phase information it is possible to simplify the information in a frequency-domain representation to generate a frequency spectrum or spectral density. A spectrum analyzer is a device that displays the spectrum, while the time-domain signal can be seen on an oscilloscope.

The power spectral density is a frequency-domain description that can be applied to a large class of signals that are neither periodic nor square-integrable; to have a power spectral density, a signal needs only to be the output of a wide-sense stationary random process.

Although "*the*" frequency domain is spoken of in the singular, there are a number of different mathematical transforms which are used to analyze time domain functions and are referred to as "frequency domain" methods. These are the most common transforms, and the fields in which they are used:

This page was last edited on 18 April 2018, at 19:29 (UTC).

Reference: https://en.wikipedia.org/wiki/Frequency_domain under CC BY-SA license.

Reference: https://en.wikipedia.org/wiki/Frequency_domain under CC BY-SA license.

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