论文标题
熵约束最大化互信息量化
Entropy-Constrained Maximizing Mutual Information Quantization
论文作者
论文摘要
在本文中，我们研究了二进制输入离散无内存通道的输出的量化，从而最大程度地提高了输入和量化输出之间的量化信息之间的相互信息。引入了多项式时间算法，可以找到真正的全局最佳量化器。这些结果适用于具有任意数量量化输出的二进制输入通道。最后，我们将这些结果扩展到二进制输入连续输出通道，并显示出足够的条件，因此单个阈值量化器是最佳量化器。提供理论结果和数值结果，以证明我们的技术合理。
In this paper, we investigate the quantization of the output of a binary input discrete memoryless channel that maximizing the mutual information between the input and the quantized output under an entropy-constrained of the quantized output. A polynomial time algorithm is introduced that can find the truly global optimal quantizer. These results hold for binary input channels with an arbitrary number of quantized output. Finally, we extend these results to binary input continuous output channels and show a sufficient condition such that a single threshold quantizer is an optimal quantizer. Both theoretical results and numerical results are provided to justify our techniques.
