最优的位量化器对于加性均匀噪声是不对称的

G. Alirezaei, R. Mathar
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引用次数: 4

摘要

在本文中,我们考虑了一个具有任意加性噪声的有幅输入信号的一比特输出量化。然后以各种方式表示容量,每种方式都表明找到最佳量化阈值q是一个极其困难的问题。对于一类以均匀分布为典型代表的噪声分布,证明了最佳量化器是不对称的。这与直觉相矛盾,直觉认为对称噪声的最佳阈值是输入分布的平均值。
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Optimal one-bit quantizers are asymmetric for additive uniform noise
In this paper, we consider one-bit output quantization of an amplitude bounded input-signal subject to arbitrary additive noise. Capacity is then represented in various ways, each demonstrating that finding the optimum quantization threshold q is an extremely difficult problem. For a class of noise distributions, of which a typical representative is the uniform distribution, it is shown that the optimum quantizer is asymmetric. This contradicts intuition, which for symmetric noise expects the optimum threshold to be the average of the input distribution.
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