与概率向量相关联的混合uniform distributions的量化
Quantization for a mixture of uniform distributions associated with probability vectors
摘要：
概率分布的量化的基本目标是减少值的数量，这些值通常是不可数的，将概率分布描述为某个有限集，从而通过离散分布来近似连续概率分布。概率分布的混合，也称为混合分布，是最佳量化的一个令人兴奋的新领域。在本文中，我们研究了三种不同的混合分布产生的均匀分布与概率向量的最佳量化。
英文摘要：
The basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability distribution to some finite set and thus approximation of a continuous probability distribution by a discrete distribution. Mixtures of probability distributions, also known as mixed distributions, are an exciting new area for optimal quantization. In this paper, we investigate the optimal quantization for three different mixed distributions generated by uniform distributions associated with probability vectors.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
