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Asymptotic analysis of optimum uniform scalar quantizers for generalized Gaussian distributions

机译:广义高斯分布的最优均匀标量量化器的渐近分析

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This paper studies the asymptotic characteristics of optimum uniform scalar quantizers as N, the number of levels, becomes large. It is shown that the length of the support region increases as (ln N)/sup 1//spl alpha//, when applied to a random variable with a generalized Gaussian density of the form p(x)=ae(-b|x|/sup /spl alpha//). Moreover, the mean-squared error is asymptotically well approximated by /spl Delta//sup 2//12, where /spl Delta/ is the step size, and decreases as (ln N)/sup 2//spl alpha///N/sup 2/.
机译:本文研究了最优的均匀标量量化器的渐近特性,其中N的水平数变大。结果表明,当将支撑区域的长度以(ln N)/ sup 1 // spl alpha //的形式增加时,将其应用到形式为p(x)= ae(-b |)的广义高斯密度的随机变量中。 x | / sup / spl alpha //)。此外,均方误差渐近地很好地近似于/ spl Delta // sup 2 // 12,其中/ spl Delta /是步长,并减小为(ln N)/ sup 2 // spl alpha /// N / sup 2 /。

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