In this paper, we study the asymptotic optimality of a low-complexity coding strategy for
Gaussian vector sources. Specifically, we study the convergence speed of the rate of such a coding
strategy when it is used to encode the most relevant vector sources, namely wide sense stationary
(WSS), moving average (MA), and autoregressive (AR) vector sources. We also study how the coding
strategy considered performs when it is used to encode perturbed versions of those relevant sources.
More precisely, we give a sufficient condition for such perturbed versions so that the convergence
speed of the rate remains unaltered
