scholarly journals Multifractal diffusion entropy analysis: Optimal bin width of probability histograms

2014 ◽  
Vol 413 ◽  
pp. 438-458 ◽  
Author(s):  
Petr Jizba ◽  
Jan Korbel
Keyword(s):  
Entropy Analysis ◽  
Diffusion Entropy

Diffusion entropy analysis in billiard systems

2019 ◽  
Vol 100 (4) ◽  
Author(s):  
Gabriel I. Díaz ◽  
Matheus S. Palmero ◽  
Iberê Luiz Caldas ◽  
Edson D. Leonel
Keyword(s):  
Entropy Analysis ◽  
Diffusion Entropy

Nonextensive Diffusion Entropy Analysis and Teen Birth Phenomena

2004 ◽  
Author(s):  
N. Scafetta ◽  
P. Grigolin
Keyword(s):  
Complex System ◽  
Time Series ◽  
Entropy Analysis ◽  
Fractal Structures ◽  
Mathematical Methods ◽  
Teen Birth ◽  
Working Definition ◽  
Diffusion Entropy ◽  
Wavelet Multiresolution Analysis ◽  
Definition Of

A complex process is often a balance between nonscaling and scaling components. We show how the nonextensive Tsallis g-entropy indicator may be interpreted as a measure of the nonscaling condition in time series. This is done by applying the nonextensive entropy formalism to the diffusion entropy analysis (DEA). We apply the analysis to the study of the teen birth phenomenon. We find that the number of unmarried teen births is strongly influenced by social processes that induce an anomalous memory in the data. This memory is related to the strength of the nonscaling component of the signal and is more intense than that in the married teen birth time series. By using a wavelet multiresolution analysis, we attempt to provide a social interpretation of this effect…. One of the most exciting and rapidly developing areas of modern research is the quantitative study of "complexity." Complexity has special interdisciplinary impacts in the fields of physics, mathematics, information science, biology, sociology, and medicine. No definition of a complex system has been universally embraced, so here we adopt the working definition, "an arrangement of parts so intricate as to be hard to understand or deal with." Therefore, the main goal of the science of complexity is to develop mathematical methods in order to discriminate among the fundamental microscopic and macroscopic constituents of a complex system and to describe their interrelations in a concise way. Experiments usually yield results in the form of time series for physical observables. Typically, these time series contain both a slow regular variation, usually called a "signal," and a rapid erratic fluctuation, usually called "noise." Historically, the techniques applied to processing such time series have been based on equilibrium statistical mechanics and, therefore, they are not applicable to phenomena far from equilibrium. Among the fluctuating phenomena, a particularly important place is occupied by those phenomena characterized by some type of self-similar or scaling-fractal structures [4]. In this chapter we show that the nonextensive Tsallis g-entropy indicator may be interpreted as a measure of the strength of the nonscaling component of a time series.

scholarly journals Diffusion entropy analysis on the scaling behavior of financial markets

2006 ◽  
Vol 367 ◽  
pp. 337-344 ◽  
Author(s):  
Shi-Min Cai ◽  
Pei-Ling Zhou ◽  
Hui-Jie Yang ◽  
Chun-Xia Yang ◽  
Bing-Hong Wang ◽  
...  
Keyword(s):  
Financial Markets ◽  
Scaling Behavior ◽  
Entropy Analysis ◽  
Diffusion Entropy

scholarly journals White Matter Injuries in Mild Traumatic Brain Injury and Posttraumatic Migraines: Diffusion Entropy Analysis

Radiology ◽  
2016 ◽  
Vol 279 (3) ◽  
pp. 859-866 ◽  
Author(s):  
Joseph Delic ◽  
Lea M. Alhilali ◽  
Marion A. Hughes ◽  
Serter Gumus ◽  
Saeed Fakhran
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
White Matter ◽  
Mild Traumatic Brain Injury ◽  
Entropy Analysis ◽  
Diffusion Entropy

Stock market stability: Diffusion entropy analysis

2016 ◽  
Vol 450 ◽  
pp. 462-465 ◽  
Author(s):  
Shouwei Li ◽  
Yangyang Zhuang ◽  
Jianmin He
Keyword(s):  
Stock Market ◽  
Entropy Analysis ◽  
Market Stability ◽  
Diffusion Entropy

scholarly journals Lévy scaling: The diffusion entropy analysis applied to DNA sequences

2002 ◽  
Vol 66 (3) ◽  
Author(s):  
Nicola Scafetta ◽  
Vito Latora ◽  
Paolo Grigolini
Keyword(s):  
Dna Sequences ◽  
Entropy Analysis ◽  
Diffusion Entropy

Multiscale Diffusion Entropy Analysis on Traffic Index Series

2014 ◽  
Vol 556-562 ◽  
pp. 3553-3557 ◽  
Author(s):  
Jing Jing Huang
Keyword(s):  
Entropy Analysis ◽  
Reliable Analysis ◽  
Diffusion Entropy ◽  
Dea Method ◽  
Scale Properties

In this paper, we present a multiscale diffusion entropy analysis (DEA) for describing the traffic fractal dynamics with a spectrum of scale exponents . The method combines DEA with moving fitting window to analyze the traffic index (TI) series in different scales and shows more details of scale properties and provides a reliable analysis. We also quantify the effects of weather, traffic peaks on scale spectrum. The results indicate clearly that at large scales, the exponents show large volatility and they all have their own scale patterns. The multiscale DEA method provides new ways to measure the TI series and distinguishes groups in different conditions.

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