Colors of noise 

White 
Pink 
Brown/Red 
Grey 
While noise is by definition derived from a random signal, it can have different characteristic statistical properties corresponding to different mappings from a source of randomness to the concrete noise. Spectral density (power distribution in the frequency spectrum) is such a property, which can be used to distinguish different types of noise. This classification by spectral density is given "color" terminology, with different types named after different colors, and is common in different disciplines where noise is an important factor (like acoustics, electrical engineering, and physics). However, different fields may use the terminology with different degrees of specificity.
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Many of these definitions assume a signal with components at all frequencies, with a power spectral density per unit of bandwidth proportional to 1/f ^{β} and hence they are examples of powerlaw noise. For instance, the spectral density of white noise is flat (β = 0), while flicker or pink noise has β = 1, and brown noise has β = 2.
Various noise models are employed in analysis, many of which fall under the above categories. AR noise or "autoregressive noise" is such a model, and generates simple examples of the above noise types, and more. The Federal Standard 1037C Telecommunications Glossary defines white, pink, blue, and black.
The color names for these different types of sounds are derived from a loose analogy between the spectrum of frequencies of sound wave present in the sound (as shown in the blue diagrams) and the equivalent spectrum of light wave frequencies. That is, if the sound wave pattern of "blue noise" were translated into light waves, the resulting light would be blue, and so on.
White noise is a signal (or process), named by analogy to white light, with equal energy per cycle (hertz).^{[1]}^{[2]} This produces a flat frequency spectrum in linear space. In other words, the signal has equal power in any band of a given bandwidth (power spectral density). For example, the range of frequencies between 40 Hz and 60 Hz contains the same amount of sound power as the range between 4000 Hz and 4020 Hz has.
A signal is considered "white" if it has a flat spectrum over a defined frequency band (such as the range of human hearing, or the frequency response of audio/visual equipment).
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The frequency spectrum of pink noise is flat in logarithmic space; it has equal power in bands that are proportionally wide.^{[3]}^{[2]} This means that pink noise would have equal power in the frequency range from 40 to 60 Hz as in the band from 4000 to 6000 Hz. Since humans hear in such a proportional space, where a doubling of frequency is perceived the same regardless of actual frequency (40–60 Hz is heard as the same interval and distance as 4000–6000 Hz), every octave contains the same amount of energy and thus pink noise is often used as a reference signal in audio engineering. That is, the human auditory system perceives approximately equal magnitude on all frequencies. The power density, compared with white noise, decreases by 3 dB per octave (density proportional to 1/f ). For this reason, pink noise is often called "1/f noise".
Since there are an infinite number of logarithmic bands at both the low frequency (DC) and high frequency ends of the spectrum, any finite energy spectrum must have less energy than pink noise at both ends. Pink noise is the only powerlaw spectral density that has this property: all steeper powerlaw spectra are infinite if integrated to the DC, low frequency end, and all flatter powerlaw spectra are infinite if integrated to the highfrequency limit.
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In fields that adopt precise definitions, the terminology "red noise", also called Brown noise or Brownian noise, will usually refer to a power density which decreases 6 dB per octave with increasing frequency (density proportional to 1/f ^{2})^{[2]} over a frequency range which does not include DC (in a general sense, does not include a constant component, or value at zero frequency). In areas where terminology is used loosely, "red noise" may refer to any system where power density decreases with increasing frequency.^{[4]}
The first definition can be generated by an algorithm which simulates Brownian motion or by integrating white noise. "Brown" noise is not named for a power spectrum that suggests the color brown; rather, the name is a corruption of Brownian motion. "Red noise" describes the shape of the power spectrum, with pink being between red and white. Also known as "random walk" or "drunkard's walk" noise.
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Blue noise is also called azure noise. Blue noise's power density increases 3 dB per octave with increasing frequency (density proportional to f ) over a finite frequency range.^{[5]}^{[2]} In computer graphics, the term "blue noise" is sometimes used more loosely as any noise with minimal low frequency components and no concentrated spikes in energy. This can be good noise for dithering,^{[6]} since retinal cells are arranged in a bluenoiselike pattern.^{[7]}
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Violet noise is also called purple noise. Violet noise's power density increases 6 dB per octave with increasing frequency^{[8]}^{[9]}^{[2]} (density proportional to f ^{2}) over a finite frequency range. It is also known as differentiated white noise.
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Grey noise is random pink noise subjected to a psychoacoustic equal loudness curve (such as an inverted Aweighting curve) over a given range of frequencies, giving the listener the perception that it is equally loud at all frequencies. This is in contrast to standard pink noise which has equal strength over a logarithmic scale of frequencies but is not perceived as being equally loud due to biases in the human equalloudness contour.
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There are also many "unofficial" colors, usually with multiple definitions
Orange noise is quasistationary noise with a finite power spectrum with a finite number of small bands of zero energy dispersed throughout a continuous spectrum. These bands of zero energy are centered about the frequencies of musical notes in whatever scale is of interest. Since all intune musical notes are eliminated, the remaining spectrum could be said to consist of sour, citrus, or "orange" notes.^{[12]}
Black noise is also called silent noise.
In telecommunication, the term noisy white has the following meanings:^{[15]}
In telecommunication, the term noisy black has the following meanings:^{[16]}
This article incorporates public domain material from the General Services Administration document "Federal Standard 1037C".
