利用分段线性比较器的量化方法

D. Kazakos, S. Makki
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引用次数: 2

摘要

本文考虑了一类具有给定分位数和任意形状的输入信号分布的鲁棒量化器的设计。量化器模型由一个比较器和一个均匀量化器组成。考虑了大量量化点的情况,我们采用Bennett和Gersho的近似来测量平均功率失真。我们证明了分段线性编译器为所有输入概率分布的类提供了鲁棒量化,只有它们的分位数指定。通过确定所需的所有参数,提供了最优的鲁棒解。对于块量化器的情况也解决了这个问题,并且我们证明了鲁棒解对应于一个分段常数输出点密度函数。最不利的输入多变量密度函数是分段均匀的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantization approach utilizing piecewise linear companders
This paper considers the design of a robust quantizer for the class of input signal distributions having given quantiles and otherwise arbitrary shape. The quantizer model that consists of a compander and a uniform quantizer is utilized. The case of large number of quantization points is considered, and we use Bennett's and Gersho's approximation to the mean rth power distortion measure. We demonstrate that the piecewise linear compander provides robust quantization for the class of all input probability distributions having only their quantiles specified. The optimum robust solution is provided through the determination of all the required parameters. The problem is resolved for the case of block quantizers as well, and we show that the robust solution corresponds to a piecewise constant output point density function. The least favorable input multivariable density function is the piecewise uniform one.
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