Noise variance for rounded two's complement product quantization

The Halyo-McAlpine discrete model for product quantization is reconstructed using an error variable set having an even number of members. It is shown in this case that the noise variance associated with a continuous model becomes an upper rather than a lower bound on the variance of the product quantization noise. The modified error set is shown to be more consistent with binary data formats such as two's complement.