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A theoretical analysis, aimed at characterizing the degradation induced bythe resampling and requantization processes applied to band-limited Gaussiansignals with flat power spectrum, available through their digitized samples, ispresented. The analysis provides an efficient algorithm for computing thecomplete {joint} bivariate discrete probability distribution associated to thetrue quantized version of the Gaussian signal and to the quantity estimatedafter resampling and requantization of the input digitized sequence. The use ofFourier transform techniques allows deriving {approximate} analyticalexpressions for the quantities of interest, as well as implementing theirefficient computation. Numerical experiments are found to be in good agreementwith the theoretical results, and confirm the validity of the whole approach.

Resampling and requantization of band-limited Gaussian stochastic signals with flat power spectrum