Noise: Pink - vs Brown (aka Red!), White,Violet,,Blue,Gray,Orange,

[alexis]

http://en.wikipedia.org/wiki/Colors_of_noise

http://en.wikipedia.org/wiki/Pink_noise

Some interesting stuff here, for those like me who have heard the terms, but wasn't really sure what they meant. The math(s) are a bit much to skim through for me, but the graphs are great, and they have audio examples!

1) Pink noise (equal power in all bandwidths that are proportionally wide) is so named, because mathematically it is between white noise (equal power in all equal bandwidths) and Brown noise (also called Red noise) which approximates Brownian motion.

2) Some amazing factoids about pink noise:
In physical systems it is present in some meteorological data series, the electromagnetic radiation output of some astronomical bodies, and in almost all electronic devices (referred to as flicker noise). In biological systems, it is present in heart beat rhythms, neural activity, and the statistics of DNA sequences. In financial systems it is often referred to as a long-term memory effect. Also, it describes the statistical structure of many natural images (images from the natural environment).[2] Recently, 1/f noise has also been successfully applied to the modeling of mental states in psychology.[3]

Richard F. Voss and J. Clarke claim that almost all musical melodies, when each successive note is plotted on a scale of pitches, will tend towards a pink noise spectrum.[4] Similarly, a generally 1/f distribution pattern has been observed in film shot length by researcher James E. Cutting of Cornell University, in the study of 150 popular movies released from 1935 to 2005.[5]In physical systems it is present in some meteorological data series, the electromagnetic radiation output of some astronomical bodies, and in almost all electronic devices (referred to as flicker noise). In biological systems, it is present in heart beat rhythms, neural activity, and the statistics of DNA sequences. In financial systems it is often referred to as a long-term memory effect. Also, it describes the statistical structure of many natural images (images from the natural environment).[2] Recently, 1/f noise has also been successfully applied to the modeling of mental states in psychology.[3]

Some other factoids I found interesting:

3)The noise that sounds like it is equally loud across the spectrum is not "Pink" noise, but rather "Gray" noise, constructed so as to be the inverse of the Fletcher Munson curves. As shown in the graphs, it looks like the "smiley face" setting of a home stereo graphic equalizer!

4) Blue noise, the opposite of pink noise (because power increases, rather than decreases, by 3dB/octave), is a not only a good noise to add for dithering (not sure why, though??), but also describes the arrangement of retinal cells in the eye which results in good visual resolution!

Something I don't understand, can someone help out with this please? Wouldn't a truly random noise distribution (defined in the article as "Brown(ian) or "Red" noise) have equal power at each frequency ... and how would that be different from "White" noise? I know I'm wrong, I'm just not seeing where.

Similarly,they describe the power density of Brownian (aka Red) noise as decreasing by 6dB/octave. But if Brownian noise is truly random, how is it that it can be described like that?

I hope someone else finds this stuff interesting, and thanks for any help with the questions above!

[Hugh Robjohns]

Wouldn't a truly random noise distribution (defined in the article as "Brown(ian) or "Red" noise) have equal power at each frequency ... and how would that be different from "White" noise? I know I'm wrong, I'm just not seeing where.

Similarly,they describe the power density of Brownian (aka Red) noise as decreasing by 6dB/octave. But if Brownian noise is truly random, how is it that it can be described like that?

It's because both the decibel scale, and normal frequency scales are described in logarithmic terms, and octaves are doublings of frequency with each increment.

Hugh

[Daniel Davis]

Random noise is pretty much anything recorded since

a)2000
b)1990
c)1980