论文标题
平均复发量化分析 - 方法省略了复发阈值选择
Averaged Recurrence Quantification Analysis -- Method omitting the recurrence threshold choice
论文作者
论文摘要
复发定量分析（RQA）是一种非线性数据分析的良好方法。在这项工作中，我们提出了一种几乎无参数RQA的新策略。该方法最终通过计算一系列阈值的RQA度量（实际上复发率）来省略阈值参数的选择。具体而言，我们测试了RQA测量确定论的能力，就其信号与噪声比的数据进行分类。我们考虑一个周期性信号，简单的混沌逻辑方程和Lorenz系统在经过测试的数据集中，其信号与噪声比的长度为$ 10^2、10^3、10^4，$和$ 10^5 $。为了使计算成为可能，开发了一种新的有效算法，以简化图形处理单元（GPU）的数值操作。
Recurrence quantification analysis (RQA) is a well established method of nonlinear data analysis. In this work we present a new strategy for an almost parameter-free RQA. The approach finally omits the choice of the threshold parameter by calculating the RQA measures for a range of thresholds (in fact recurrence rates). Specifically, we test the ability of the RQA measure determinism, to sort data with respect to their signal to noise ratios. We consider a periodic signal, simple chaotic logistic equation, and Lorenz system in the tested data set with different and even very small signal to noise ratios of lengths $10^2, 10^3, 10^4,$ and $10^5$. To make the calculations possible a new effective algorithm was developed for streamlining of the numerical operations on Graphics Processing Unit (GPU).
