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中文摘要：
健康和有疾病的心率变异性（HRV）参数有明显差异，计算关联维是识别这种差异的一种重要手段。用传统的G—P算法计算关联维时，嵌入维数m、延迟时间τ、及序列长度N等参数的选取会对最终计算结果有很大影响。本文从理论和实验方面论述了如何选取这些参数以获得正确的结果，并且将其应用于正常组和心率不齐疾病组进行对照，结果显示关联维可以有效地表征由于疾病对于心脏节律造成的影响。
英文摘要：
There are differences in nonlinear parameters between HRV signals of healthy persons and arrhythmia patients. And it is a significant method to recognise the differences by calculating the correlation dimension （D2）. When using the traditional G-P algorithm to calculate D2, the choice of these parameters, including the embedding dimension m, time delay τ and data length N, greatly influence the final results. The paper discusses how to select these parameters in both theoretical and experimental ways, and applies these methods to calculating D2 of normal and arrhythmia HRV signals. The results show that D2 can effectively characterize the influence of heart diseases.
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Alteration in scaling behavior of short-term heartbeat time series for professional shooting athlete
A new measure to characterize multifractality of sleep electro- encephalogram, Chinese Science Bulle
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