一维双分量GMM的分段均匀量化

A. Jovanovic, Z. Perić, N. Vučić
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引用次数: 0

摘要

本文提出了具有一维双分量高斯混合模型概率密度函数的振幅的分段均匀标量量化(PUSQ)方法。对于所提出的模型,我们还推导了均方误差(失真D)和信噪比(SQNR)的渐近公式。此外,对于在理论模型制定过程中引入的约束,我们根据均方误差或SQNR对PUSQ进行了数值优化。特别是,对于给定的约束,我们确定了最大化SQNR的PUSQ范围之间的阈值。由于在文献中没有经常考虑用GMM pdf量化振幅,我们相信本文提出的结果将有助于更好地了解这个问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Piecewise Uniform Quantization for One-Dimensional Two-Component GMM
In this paper we propose piecewise uniform scalar quantization (PUSQ) for amplitudes having one dimensional two-component Gaussian mixture model probability density function (GMM pdf). For the proposed model we also derive asymptotic formulas for the mean-square error (distortion D) and signal to quantization noise ratio (SQNR). In addition, for the constraints introduced during the theoretical model formulation, we perform a numerical optimization of PUSQ in terms of the mean square-error, or, equivalently, in terms of the SQNR. In particular, for the given constraints we determine the threshold between ranges of PUSQ that maximizes the SQNR. As quantization of amplitudes with GMM pdf has not been frequently considered in the literature, we believe that the results presented in this paper will help to gain a better insight into this issue.
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