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The table shows the probabilities, quantization thresholds, and the corresponding bin-average values for 1-bit, 2-bit, and 3-bit quantization processes for a Gaussian random variable with zero mean and unity standard deviation.
In fixed-point representation, it is beneficial to scale up the smallest magnitude of the bin-average values, since this will simplify the implementation and slightly increase the precision.
For example, in a 2-bit quantization process, 0.32 is promoted to 1.00, and 1.27 is promoted to 1.27 over 0.32, whish is 3.91.
The other quantization processes will follow a similar pattern.
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IEEE/ICACT20210153 Slide.09
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