【摘要】 为了解决经典的优化Grassberger-Procaccia关联维算法存在的运算量大、耗费时间长且在实际中难以应用的问题,提出了一种关联维快速算法.结果表明,该快速算法在误差很小的范围内,速度却可提高上百甚至上千倍,为关联维计算的实际应用开辟了新的前景.更多还原

【Abstract】 The optimized classic Grassberger-Procaccia correlation dimension algorithm involves tremendous calculation, time-consuming and limited practicability. To overcome the shortcomings, a fast algorism of correlation dimension is introduced in this paper. The results show that this algorithm can increase the calculating speed hundreds or thousands of times in a small error range. All of these indicate a new prospect for the practical use of correlation dimensional calculation.更多还原