Quantization noise
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Quantization noise is a noise error introduced by quantization in the analogue to digital conversion (ADC) process in telecommunication systems and signal processing. It is a rounding error between the analogue input voltage to the ADC and the output digitized value. The noise is non-linear and signal-dependent. It can be modeled in several different ways.
It is expressed as a root-mean-square error as
- [ N_Q = \frac} \right )^2 } \cdot R_\mathrm^2} ]
In an ideal analogue-to-digital converter, the signal-to-noise ratio (SNR) can be calculated from
- [\mathrm} = 20 \log_(2^n) \approx 6.02 \cdot n\ \mathrm ]
This comes from a model of quantization noise in an ideal ADC where the quantization error is uniformly distributed between -1/2 LSB and +1/2 LSB. The signal is also assumed to have a uniform distribution covering all quantization levels, and the most common test signals that fulfill this are full amplitude triangle waves and sawtooth waves.
When the input signal is a full-amplitude sine wave the distribution of the signal is no longer uniform, and the corresponding equation is instead
- [ \mathrm} = \left ( 1.761 + 6.02 \cdot Q \right )\ \mathrm ]
- [Quantization Noise] ([file info])
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- * Problems listening to the file? See [Media helpmedia help].
See also
External links
- [The Relationship of Dynamic Range to Data Word Size in Digital Audio Processing]
- [Round-Off Error Variance] - derivation of noise power of q2/12 for round-off error
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