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The enormous growth in popularity of peer-to-peer applications has recently introduced great interest in understanding the associated traffic workload and behavior. The goal of this work is determining the fundamental dynamics characterizing such traffic that can be used to develop simple and effective prediction models and to illustrate and describe fundamental performance issues. The discovery of...
This paper analysis the chaotic dynamical properties of network traffic based on the self-similarity characteristic of the Internet traffic. The phase space of the traffic time serials is reconstructed and the correlation dimension is analyzed, which indicate that the dynamical system has finite degree of freedom and a positive maximum Lyapunov exponent. The chaotic characteristic of the traffic is...
In this paper, the dynamic complexity of a three-species ecological system with the Beddington-DeAngelis functional response is studied by using Lyapunov exponents, and bifurcation diagrams. Furthermore, the effects of intraspecies density dependence (IDD) on the dynamics of the model are investigated. It has been found that the addition of IDD to a three-species ecological model stabilizes the system,...
In this paper, the real network traffic is analyzed about its chaotic dynamic properties and the traffic signals are reconstructed using FBM based fractal interpolation algorithm. The self-similarity of network traffic is analyzed by estimating the value of Hurst exponent and the traffic time series is reconstructed as a phase trajectory by properly choosing some parameters. Through the reconstructed...
A wide variety of methods based on fractal, entropic or chaotic approaches have been applied to the analysis of complex physiological time series. In this paper, we show that fractal and entropy measures are poor indicators of nonlinearity for gait data and heart rate variability data. In contrast, the noise titration method based on Volterra autoregressive modeling represents the most reliable currently...
This paper deals with the problem of exponential stability for a class of discrete-time recurrent neural networks with time-varying delay by employing an improved free-weighting matrix approach. The relationship among the time-varying delay, its upper bound and their difference is taken into account. As a result, a new and less conservative delay-dependent stability criterion is obtained without ignoring...
This paper proves that Shanghai securities business is a biased stochastic market with chaos-fractal characteristics by using R/S analysis. The fluctuations of composite index are with obvious self-similarity and long-term memory. The Hurst exponent of Shanghai securities composite index is calculated and a waving period for 450 days in Shanghai securities business is found through the study of V...
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