Power-Law Fluctuation in Expressway Traffic Flow: Detrended Fluctuation Analysis

2006 ◽  
Vol 75 (3) ◽  
pp. 034002 ◽  
Author(s):  
S. Tadaki ◽  
M. Kikuchi ◽  
A. Nakayama ◽  
K. Nishinari ◽  
A. Shibata ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Power Law ◽  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Detrended Fluctuation

Evaluation of Wellness by Detrended Fluctuation Analysis of Heartbeats

2010 ◽  
Author(s):  
Toru Yazawa ◽  
Yukio Shimoda ◽  
Tomoo Katsuyama
Keyword(s):  
Power Law ◽  
Healthy Subjects ◽  
Detrended Fluctuation Analysis ◽  
Thermal Therapy ◽  
Fluctuation Analysis ◽  
Premature Ventricular Contractions ◽  
Quality Of Recovery ◽  
Healthy State ◽  
Detrended Fluctuation

We used detrended fluctuation analysis (DFA), which was originally developed by Peng et al. (1995) to check power-law characteristics, to study the heartbeats of various subjects. Our purpose was to determine whether DFA is a useful method for the evaluation of a subject’s quality of recovery from cardiovascular-related illness and transition to a normal healthy state. Here, we report on subjects who underwent rehabilitation thermal therapy, subjects who developed premature ventricular contractions, and other subjects, including healthy subjects. The perceived level of wellness varies among subjects because the physiology of no 2 individuals is identical. However, several case studies have shown how wellness of subjects can be evaluated using heartbeat recordings. We conclude that DFA is a new, useful numerical method for quantifying the degree of wellness and the transition from sickness to wellness.

THE ORTHOGONAL V-SYSTEM DETRENDED FLUCTUATION ANALYSIS

2011 ◽  
Vol 10 (02) ◽  
pp. 189-206 ◽  
Author(s):  
AIJING LIN ◽  
PENGJIAN SHANG ◽  
HUI MA
Keyword(s):  
Long Range ◽  
Power Law ◽  
Detrended Fluctuation Analysis ◽  
Fluctuation Analysis ◽  
Smoothing Algorithm ◽  
Scaling Exponents ◽  
Long Range Correlations ◽  
Piecewise Function ◽  
Robust Techniques ◽  
Detrended Fluctuation

The Detrended Fluctuation Analysis (DFA) and its extensions (MF-DFA) have been proposed as robust techniques to determine possible long-range correlations in self-affine signals. However, many studies have reported the susceptibility of DFA to trends which give rise to spurious crossovers and prevent reliable estimations of the scaling exponents. Lately, several modifications of the DFA method have been reported with many different techniques for eliminating the monotonous and periodic trends. In this study, a smoothing algorithm based on the Orthogonal V-system (OVS) is proposed to minimize the effect of power-law trends, periodic trends, assembled trends and piecewise function trends. The effectiveness of the new method is demonstrated on monofractal data and multifractal data corrupted with different trends.

scholarly journals DETRENDED FLUCTUATION ANALYSIS OF THE TCP-RED ALGORITHM

2009 ◽  
Vol 19 (12) ◽  
pp. 4237-4245 ◽  
Author(s):  
XI CHEN ◽  
SIU-CHUNG WONG ◽  
CHI K. TSE ◽  
LJILJANA TRAJKOVIĆ
Keyword(s):  
Time Series ◽  
Long Range ◽  
Power Law ◽  
Detrended Fluctuation Analysis ◽  
Time Series Data ◽  
Analytical Models ◽  
Series Data ◽  
Fluctuation Analysis ◽  
Scaling Exponent ◽  
Detrended Fluctuation

It has been observed that Internet gateways employing Transport Control Protocol (TCP) and the Random Early Detection (RED) control algorithm may exhibit instability and oscillatory behavior. Most control methods proposed in the past have been based on analytical models that rely on statistical measurements of network parameters. In this paper, we apply the detrended fluctuation analysis (DFA) method to analyze stability of the TCP-RED system. The DFA is used to analyze time-series data and generate power-law scaling exponents, which indicate the long-range correlations of the time series. We quantify the stability of the TCP-RED system by examining the variation of the DFA power-law scaling exponent when the system parameters are varied. We also study the long-range power-law correlations of TCP window periods.

Scaling analysis of hyperchaotic time series

2017 ◽  
Vol 28 (07) ◽  
pp. 1750094 ◽  
Author(s):  
J. S. Murguía
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Power Law ◽  
Detrended Fluctuation Analysis ◽  
Dynamical Evolution ◽  
Fluctuation Analysis ◽  
Discrete Wavelet ◽  
Scaling Analysis ◽  
Detrended Fluctuation ◽  
Hyperchaotic Systems

The time series of the states of several well-known hyperchaotic systems are analyzed numerically using the detrended fluctuation analysis based on the discrete wavelet transform. We report the finding of significant scaling behaviors (power-law like) in some of these time series, which can be used as an additional characteristic distinguishing the dynamical evolution of such systems.

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