基于G.P算法的关联维计算中参数取值的研究

从理论和实践两个方面对基于G．P算法的关联维计算中参数的取值问题进行了研究。分析了重构相空间维数m的取值原则;提出了标量r的取值范围和取值序列;对数据序列长度n的取值分别从理论和应用两个方面进行了探讨。所做的工作有益于分形理论在水声信号处理、雷达信号处理、地震信号分析、目标识别等领域的应用研究。

Study of the Parameters Used in Calculating Correlative Dimension Based on G.P Algorithm

In this paper, the parameters used in calculating correlative dimension with C. P algorithm are studied. The criterion of the dimension of the phase space reconstructed is discussed. The volume of the data-series used in calculating the correlative dimension is analyzed based on theory and application. The band of the parameter r and its data-series is proposed. Some conclusions are resulted in this paper. The results will be useful for the application of fractal theory in radar signal processing, seismic data processing, underwater acoustic signal analyzing, target recognition and other fields.