Add to ORKGWe present a new method to estimate the Hurst parameter. The method exploits the form of the autocorrelation function for second-order self-similar processes and is based on one-pass digital filtration. We compare the performance and properties of the new method with that of the most common methods
The optimal computer network performance models require accurate traffic models, which can capture t...
In order to estimate the Hurst parameter of Internet traffic data, it has been recently proposed a l...
We consider the problem of estimating the Hurst parameter for long-range dependent processes using w...
Abstract. We present a new method to estimate the Hurst parameter. The method exploits the form of t...
We present a new method to estimate the Hurst pa-rameter of the increment process in network traffic...
We present a new method to estimate the Hurst parameter of the increment process in network traffic ...
The Hurst parameter H characterizes the degree of long-range dependence (and asymptotic self-similar...
Abstract- The intensity of long-range dependence (LRD) of the communications network traffic can be ...
Abstract: Data trafc traces are known to be bursty with long range dependence. The exact self-simila...
A maximum likelihood estimation method implemented in S-PLUS (S-MLE) to estimate the Hurst coefficie...
The aim of this paper is to estimate the Hurst parameter of Fractional Gaussian Noise (FGN) using Ba...
We present a new method to estimate the Hurst parameter of certain classes of random processes. Our...
In this paper we analyze a wavelet based method for the estimation of the Hurst parameter of synthet...
We present some iterative method for estimation of the scale and Hurst parameters which is addressed...
Self-similarity analysis and anomaly detection in networks are interesting fields of research and sc...
The optimal computer network performance models require accurate traffic models, which can capture t...
In order to estimate the Hurst parameter of Internet traffic data, it has been recently proposed a l...
We consider the problem of estimating the Hurst parameter for long-range dependent processes using w...
Abstract. We present a new method to estimate the Hurst parameter. The method exploits the form of t...
We present a new method to estimate the Hurst pa-rameter of the increment process in network traffic...
We present a new method to estimate the Hurst parameter of the increment process in network traffic ...
The Hurst parameter H characterizes the degree of long-range dependence (and asymptotic self-similar...
Abstract- The intensity of long-range dependence (LRD) of the communications network traffic can be ...
Abstract: Data trafc traces are known to be bursty with long range dependence. The exact self-simila...
A maximum likelihood estimation method implemented in S-PLUS (S-MLE) to estimate the Hurst coefficie...
The aim of this paper is to estimate the Hurst parameter of Fractional Gaussian Noise (FGN) using Ba...
We present a new method to estimate the Hurst parameter of certain classes of random processes. Our...
In this paper we analyze a wavelet based method for the estimation of the Hurst parameter of synthet...
We present some iterative method for estimation of the scale and Hurst parameters which is addressed...
Self-similarity analysis and anomaly detection in networks are interesting fields of research and sc...
The optimal computer network performance models require accurate traffic models, which can capture t...
In order to estimate the Hurst parameter of Internet traffic data, it has been recently proposed a l...
We consider the problem of estimating the Hurst parameter for long-range dependent processes using w...