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METHOD FOR ENCODING BASED ON MIXTURE OF VECTOR QUANTIZATION AND NEAREST NEIGHBOR SEARCH USING THEREOF

机译:基于矢量量化和近邻搜索的混合编码方法

摘要

The present invention relates to a method for encoding a candidate vector for searching for a neighbor that is nearest to a query in a candidate dataset, the method comprising a normalization step of normalizing an input vector to obtain a direction vector and vector energy; a quantization step of quantizing the direction vector to obtain a code word and a residual vector; a step of repeating the normalization step and the quantization step, as many times as a predetermined number of encoding times, by using the residual vector as an input vector; and a step of encoding the candidate vector by using one or more code words and energy of one or more vectors resulting from the repetition. According to the present invention, a dataset having a very wide range of energy values can be effectively approximated and higher precision thereof can be obtained.
机译:本发明涉及一种用于对候选向量进行编码的方法,该候选向量用于搜索候选数据集中最接近查询的邻居。该方法包括归一化步骤,该归一化步骤对输入向量进行归一化以获得方向向量和向量能量。量化步骤,对方向向量进行量化以获得码字和残差向量;通过使用残差矢量作为输入矢量,将标准化步骤和量化步骤重复预定编码次数的步骤;通过使用一个或多个代码字和重复产生的一个或多个矢量的能量对候选矢量进行编码的步骤。根据本发明,可以有效地近似具有非常宽的能量值范围的数据集,并且可以获得其更高的精度。

著录项

  • 公开/公告号US2020226137A1

    专利类型

  • 公开/公告日2020-07-16

    原文格式PDF

  • 申请/专利权人 ODD CONCEPTS INC.;

    申请/专利号US201716499789

  • 发明设计人 WAN LEI ZHAO;SAN WHAN MOON;

    申请日2017-06-20

  • 分类号G06F16/2455;G06F16/22;

  • 国家 US

  • 入库时间 2022-08-21 11:25:29

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