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Here, we provide a unified framework for numerical analysis of the stochastic nonlinear fractional diffusion equation driven by fractional Gaussian noise with Hurst index $H\in(0,1)$. A novel estimate of the second moment of the stochastic integral with ...

Fractional Gaussian noise models the time series with long-range dependence; when the Hurst index $H\in(1/2,1)$, it has positive correlation reflecting a persistent autocorrelation structure. This paper studies the numerical method for solving the ...

Due to the relevance of self-similarity analysis in several research areas, there is an increased interest in methods to generate realizations of self-similar processes, namely in the ones capable of simulating long-range dependence. This article ...

Fractal Brownian motion, also called fractional Brownian motion fBm, is a class of stochastic processes characterized by a single parameter called the Hurst parameter, which is a real number between zero and one. fBm becomes ordinary standard Brownian ...

This paper addresses three models of traffic based on fractional Gaussian noise (fGn). The first is the standard fGn (fGn for short) that is characterized by a single Hurst parameter. The second is the generalized fGn (GfGn) indexed by two parameters. ...

This paper is presented and analysed an algorithm for modeling self-similar Ethernet traffic, based on the fractional Gaussian noise (FGN) and wavelet transformation. The algorithm uses a second-order approximation for calculation of the power spectrum ...

The mutual information between a stochastic signal and this signal plus a fractional Brownian motion (described as an additive fractional Gaussian noise channel) is expressed as the error of an estimation problem that can be naturally associated with ...

This paper introduces a system for synthesizing fractional Gaussian noise (FGN) based on two approaches in the platform of MATLAB. One is empirical mode decomposition (EMD) and the other correlation method. The system can be used to simulate FGN and ...

In the paper is presented an algorithm of Durbin-Levinson for self-similar network traffic simulation. The key problem of self-similar processes studying is estimating the Hurst parameter. Determination the best Hurst techniques in the sense of Hurst ...

The Hurst exponent (H) was estimated for series of 256 time intervals produced by human participants, collected in 5 sessions performed on different days. Each series was obtained during the continuation phase following synchronization with 25 ...

The traffic engineering of IP networks requires accurate characterization and modeling of network traffic, due to the growing diversity of multimedia applications and the need to efficiently support QoS differentiation in the network. In recent years ...

Simulation studies are used to evaluate the impact of the distributional and correlational characteristics of traffic arrival processes on the performance of network routing elements. It is shown that synthetic traffic models that capture only the ...

Abstract: We present a new model for aggregated network traffic based on /spl alpha/-stable self-similar processes which captures the burstiness and the long range dependence of the data. We show how the fractional Gaussian noise assumption fails and ...