This paper describes an analysis of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view of network traffic conditions in analyzing the degree of long-range dependence (LRD) of IP-network traffic, this paper used a self-organizing scheme-based...

This research investigates long memory financial equity markets using three heuristic methodologies namely a proposed modified variance time-aggregated plot, modified rescaled-range plot and periodogram approaches. The intensity of the long memory process is quantified in terms of Hurst...

Song et al. [Self-similarity of complex networks, Nature 433 (2005) 392–395] have recently used a version of the box-counting method, called the node-covering method, to quantify the self-similar properties of 43 cellular networks: the minimal number NV of boxes of size ℓ needed to cover all...

We explore the correlation-structure of a large class of random processes, driven by non-Gaussian Lévy noise sources with possibly infinite variances. Examples of such processes include Lévy motions, Lévy-driven Ornstein–Uhlenbeck motions, Lévy-driven moving-average processes, fractional...

We demonstrate that continuous-time FARIMA processes with α-stable noise provide a new stochastic tool for studying the solar flare phenomenon in the framework of fractional Langevin equation. Simple computer tests to check the origins of α-stability and self-similarity are implemented for...

We introduce a new measure for capital market efficiency. The measure takes into consideration the correlation structure of the returns (long-term and short-term memory) and local herding behavior (fractal dimension). The efficiency measure is taken as a distance from an ideal efficient market...

The Bak–Sneppen model of co-evolution is used to derive synthetic time series with a priori specified fractal dimension (or Hurst exponent) through a mixing of processes in various lattice dimensions. Both theoretical and numerical analyses concern the avalanches at the critical threshold and...

An algorithm for calculating generalized fractal dimension of a time series using the general information function is presented. The algorithm is based on a strings sort technique and requires O(Nlog2N) computations. A rough estimate for the number of points needed for the fractal dimension...

We demonstrate that the methods of signal (time series) analysis developed in nonlinear and symbolic dynamics when applied to financial data in Econophysics give new possibilities of interpretation of those data. Analogies with interpretation of biosignals in Medical Physics may be observed....