Quantization error
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Quantization (signal processing)
elements. Rounding and truncation are typical examples of quantization processes. Quantization is involved to some degree in nearly all digital signal processing...
Dither
dithering is an intentionally applied form of noise used to randomize quantization error, preventing large-scale patterns such as color banding in images....
Mean square quantization error
Mean square quantization error (MSQE) is a figure of merit for the process of analog to digital conversion. In this conversion process, analog signals...
Analog-to-digital converter
signal. The conversion involves quantization of the input, so it necessarily introduces a small amount of quantization error. Furthermore, instead of continuously...
Discretization error
resulting error is called aliasing. Discretization error, which arises from finite resolution in the domain, should not be confused with quantization error, which...
Audio bit depth
implementations, variations in bit depth primarily affect the noise level from quantization error—thus the signal-to-noise ratio (SNR) and dynamic range. However, techniques...
Continuous uniform distribution
distributed random variables. In analog-to-digital conversion, a quantization error occurs. This error is either due to rounding or truncation. When the original...
Vector quantization
Vector quantization (VQ) is a classical quantization technique from signal processing that allows the modeling of probability density functions by the...
Mean squared error
absolute error, or those based on the median. Bias–variance tradeoff Hodges' estimator James–Stein estimator Mean percentage error Mean square quantization error...
Signal-to-quantization-noise ratio
strength and the quantization error (also known as quantization noise) introduced in the analog-to-digital conversion. As SQNR applies to quantized signals, the...