在k维欧氏空间Rk中，给定一个有限子集W及一个向量ｘ，如何搜索W中与ｘ距离最近的向量，具有重要的实际应用价值，尤其在图象的矢量量化编码、神经网络模式识别[１]等问题中，快速搜索起决定性的作用。在分析已有快速搜索算法的基础上，给出一种新的快速搜索算法，该算法利用图象相邻块的码书地址，作为当前块的预测值，使搜索空间缩小更快。

Given a finite subset W and a vector x both in k-dimension space, the method to fast locate the vector in W closest to x is of great value in applications. The fast search method plays an important role in the fields such as vector quantization method and pattern recognition using neural network. Based on the analysis of the fast search algorithm in Ref.[6], a new fast search algorithm is presented. Using the codebook addresses of neighboring image blocks as the predicting codebook address of current image block, the search space can be reduced more dramatically.