Ohashi Kyoko, Nunes Amaral Luís A, Natelson Benjamin H, Yamamoto Yoshiharu
Educational Physiology Laboratory, Graduate School of Education, University of Tokyo, Tokyo 113-0033, Japan.
Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Dec;68(6 Pt 2):065204. doi: 10.1103/PhysRevE.68.065204. Epub 2003 Dec 24.
We generalize the wavelet transform modulus maxima approach in order to analyze positive and negative changes separately and show different singularity spectra depending on the direction of changes in (i) human heartbeat interval data during sympathetic blockade, (ii) time series of daytime human physical activity of healthy individuals (but not of patients with debilitating fatigue), and (iii) daily stock price records of the Nikkei 225 in the period 1990-2002--but not of the S&P 500. We conclude that the analysis of asymmetrical singularities provides deeper insights into the underlying complexity of real-world signals that can greatly enhance our understanding of the mechanisms determining the systems' dynamics.
我们推广了小波变换模极大值方法，以便分别分析正向和负向变化，并根据以下方面变化的方向显示不同的奇异性谱：(i) 交感神经阻滞期间的人体心跳间隔数据；(ii) 健康个体（而非患有衰弱性疲劳的患者）白天身体活动的时间序列；以及(iii) 1990 - 2002年期间日经225指数的每日股价记录——但不包括标准普尔500指数。我们得出结论，对不对称奇异性的分析能更深入地洞察现实世界信号的潜在复杂性，这可以极大地增进我们对决定系统动态机制的理解。
