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Lower bound on the mean-squared error in oversampled quantization of periodic signals using vector quantization analysis

机译:使用矢量量化分析的周期信号过采样量化中均方误差的下限

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摘要

Oversampled analog-to-digital conversion is a technique which permits high conversion resolution using coarse quantization. Classically, by lowpass filtering the quantized oversampled signal, it is possible to reduce the quantization error power in proportion to the oversampling ratio R. In other words, the reconstruction mean-squared error (MSE) is in /spl Oscr/(R/sup -1/). It was recently found that this error reduction is not optimal. Under certain conditions, it was shown on periodic bandlimited signals that an upper bound on the MSE of optimal reconstruction is in /spl Oscr/(R/sup -2/) instead of /spl Oscr/(R/sup -1/). In the present paper, we prove on the same type of signals that the order /spl Oscr/(R/sup -2/) is the theoretical limit of reconstruction as an MSE lower bound. The proof is based on a vector-quantization approach with an analysis of partition cell density.
机译:过采样的模数转换是一种允许使用粗量化实现高转换分辨率的技术。经典地,通过对量化的过采样信号进行低通滤波,可以降低与过采样率R成比例的量化误差功率。换句话说,重建均方误差(MSE)为/ spl Oscr /(R / sup -1 /)。最近发现,这种错误减少不是最佳的。在某些条件下,在周期性带宽限制信号上显示,最佳重构的MSE的上限位于/ spl Oscr /(R / sup -2 /)中,而不是/ spl Oscr /(R / sup -1 /)中。在本文中,我们在相同类型的信号上证明了/ spl Oscr /(R / sup -2 /)阶数是重构为MSE下限的理论极限。该证明基于矢量量化方法,并分析了分区单元的密度。

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