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A Modified Fast Vector Quantization Algorithm Based on Nearest Partition Set Search

机译:基于最近分区集搜索的修改快速矢量量化算法

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In this paper we propose a modification to a fast vector quantization algorithm based on nearest partition set search. The fast algorithm searches the codebook to find the nearest set of codevectors for each codevector in the codebook. The nearest set of codevectors is called nearest set partition (NPS) which calculated each iteration. During each iteration the fast algorithm searches the NPS instead of searching the codebook which save training time. The NPS algorithm does well but with large codebook the saved timed consumed in calculating the NPS. So we proposed a modified algorithm to overcome this problem. The experimental results indicate that variation of NPS is slow with iteration. According to our results the calculation of NPS in each iteration is not necessary which save more training time without affecting the codebook quality.
机译:在本文中,我们提出了基于最近分区集搜索的快速矢量量化算法的修改。快速算法搜索码本以查找码本中的每个Codevector的最近的Codevectors集合。最近的一组Codevectors称为计算每个迭代的最近设置分区(NPS)。在每次迭代期间,快速算法搜索NPS而不是搜索节省培训时间的码本。 NPS算法很好,但大码本在计算NPS时消耗的保存定时。所以我们提出了一种修改的算法来克服这个问题。实验结果表明,NPS的变化速度速度慢。根据我们的结果,不需要在每次迭代中的NPS计算,在不影响码本质量的情况下保存更多的培训时间。

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