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Is noise with uniform distribution present in some real-life applications?

It seems that most of the internet sources describe uniform noise as something theoretical.

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Typically, when a real value $x$ from a sensor is discretized ($x_Q$) with a uniform quantizer, the error $x-x_Q$ is likely to be uniformly distributed.

Caveat: as commented by @bone, this can be stated in precise terms, see for instance:

In this paper, a necessary and sufficient condition is given to model the output of a quantizer as an infinite-precision input and an additive, uniform, white noise. The statistical properties of the quantization error are studied, and a detailed analysis for Gaussian distributed inputs is given.

  • Statistical Theory of Quantization, Bernard Widrow, Istvan Kollar, Ming-Chang Liu, 1996

The effect of uniform quantization can often be modeled by an additive noise that is uniformly distributed, uncorrelated with the input signal, and has a white spectrum. This paper surveys the theory behind this model, and discusses the conditions of its validity. The application of the model to floating-point quantization is demonstrated.

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    $\begingroup$ Strictly speaking, the quantization error is not a random signal if the input is known. It is modeled as uniform noise because it simplifies the analysis and gives good enough results. $\endgroup$
    – bone
    Commented Feb 21, 2017 at 9:35
  • $\begingroup$ You notice that I wrote "likely" to make it short (now put in bold).I have now added some references. $\endgroup$ Commented Feb 21, 2017 at 9:57

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