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On the Asymptotic Optimality of a Low-Complexity Coding Strategy for WSS, MA, and AR Vector Sources
Jesús Gutiérrez-Gutiérrez1, Marta Zárraga-Rodríguez1, Xabier Insausti1
1Tecnun, University of Navarra, Paseo Manuel Lardizábal 13, 20018 San Sebastián, Spain.
Abstract:
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.
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