基于KDC树的高阶相关函数计算

摘要

高阶相关函数的计算复杂度随维度增加呈指数增长.为此,提出一种改进的高阶相关函数计算方法.在KDC树的数据结构基础上,设计剪枝搜索算法.针对三点相关函数给出该算法的具体实现,利用多线程并行技术对其进行加速,从而优化高阶相关函数的计算.实验结果验证了该方法的正确性和有效性.%The complexity of higher order correlation function increases exponentially with the growth of the dimension. An improved high-order correlation function calculation method is presented in this paper. A new pruning research algorithm based on the KDC-tree data structure is designed. The implementation of three points correlation function is given, and it is accelerated with parallel technology to optimize the calculation of high-order correlation function. Experimental results validate the correctness and efficiency of this method.