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Multifractality of the Lorenz system

Physical Review E, 1996
We use the unstable periodic orbit expansion of the dynamical \ensuremath{\zeta} function to find the multifractal spectra f(\ensuremath{\alpha}) and g(\ensuremath{\Lambda}) for the Lorenz system at (r,\ensuremath{\sigma},b)=(28,10,8/3) and also for an incomplete, generalized Baker's map with the topology of the Lorenz system. \textcopyright{} 1996 The
, Wiklund, , Elgin
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MASS MULTIFRACTAL CHARACTERIZATION OF BLOOD VESSEL SYSTEMS

Fractals, 1996
The blood vessel system as measured on kidney1 and placenta arteries2,3 is known to be a non-homogeneous fractal with a distribution of local dimensions. We interpret this distribution as a mass multifractal property and we have therefore examined the average of the masses Mi(r) and their qth moments within boxes of increasing size r. The centers i of
Jestczemski, F., Sernetz, M.
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Multifractal Characterization of Soil Pore Systems

Soil Science Society of America Journal, 2003
Spatial arrangement of soil pores determines soil structure and is important to model soil processes. Geometric properties of individual pores can be estimated from thin sections, but there is no satisfactory method to quantify the complexity of their spatial arrangement.
Adolfo N. D. Posadas   +3 more
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Multifractal Statistics of Mesoscopic Systems

Journal of Statistical Physics, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Multifractal Analysis of Disperse Polymetallic Systems

Doklady Chemistry
Multifractal analysis is one of the tools for studying complex objects with self-similar structure, such as dispersed polymetallic systems. This paper deals with the application of multifractal analysis to describe and evaluate the characteristics of dispersed polymetallic systems (Fe-Al-Co, Fe-Al-Cr, Fe-Al-Mo) obtained by galvanic substitution.
M.E. KOLPAKOV   +2 more
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Irreversibility, diffusion and multifractal measures in thermostatted systems

Chaos, Solitons & Fractals, 1997
Abstract Non-equilibrium macroscopic processes are irreversible, so that diffusion coefficients are always positive. Here we show how irreversible behaviour arises from reversible microscopic dynamics in some thermostatted systems, the Lorentz gas in an external field, colour diffusion and planar Couette flow in N-particle systems.
C. P. DETTMANN   +2 more
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Multifractional Random Systems on Fractal Domains

2011
In this paper, the effect of the domain geometry on the local regularity/singularity properties of the solution to the trace of a multifractional pseudodifferential equation on a fractal domain is studied. The singularity spectrum of the Gaussian solution to this type of models is trivial due to regularity assumptions on the variable order of its ...
José Miguel Angulo   +1 more
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Multifractal analysis of transients in power systems

2000 Canadian Conference on Electrical and Computer Engineering. Conference Proceedings. Navigating to a New Era (Cat. No.00TH8492), 2002
This paper presents the variance fractal dimension trajectory (VFDT) approach to studying nonstationary transients in power system. Experiments show that multifractal analysis based on the VFDT is efficient for characterizing most of the transient types found in power system signals and data reduction can be realized by simply changing the window ...
J. Chen, W. Kinsner
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Modeling multifractal traffic with stochastic L-systems

Global Telecommunications Conference, 2002. GLOBECOM '02. IEEE, 2003
This paper proposes a novel multifractal traffic model, and an associated parameter fitting procedure, based on stochastic L-systems, which were introduced by biologist A. Lindenmayer (1968) as a method to model plant growth. We provide a detailed comparison with a related multifractal model based on conservative cascades.
P. Salvador, A. Nogueira, R. Valadas
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Multifractal Security Analysis of Cyberphysical Systems

2021
In this paper authors propose to use multifractal analysis and Kalman filter for security analysis of cyberphysical systems (CPS). First stage of the proposed approach is data reduction caused by time series processing. The second stage is anomaly detection and the third stage is attack prediction.
Zegzhda, D.   +2 more
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