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A self-similar Gaussian process
Random Operators and Stochastic Equations, 2014Abstract. In this paper we introduce and study a self-similar Gaussian process denoted by S H
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Self-similarity in max/average aggregated processes
2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512), 2004Second-order self-similar processes are fully statically characterized by their activity factor and Hurst parameter, which are usually extracted from the computation of the autocovariance function of the process at different aggregation levels. Unfortunately, such an extraction procedure is difficult to be performed on experimental data or tested in ...
Mazzini G., Rovatti R., Setti G.
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Fast simulation of self-similar and correlated processes
Mathematics and Computers in Simulation, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Maria Estrella Sousa-Vieira +5 more
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Demixing multivariate-operator self-similar processes
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015Operator self-similarity naturally extends the concepts of univariate self-similarity and scale invariance to multivariate data. Beyond a vector of Hurst parameters, operator self-similarity models also involve a mixing matrix. The present contribution aims at estimating the collection of Hurst parameters in the case where the mixing matrix is not ...
Gustavo Didier +2 more
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Self‐Similar Random Measures III – Self‐Similar Random Processes
Mathematische Nachrichten, 1991AbstractThis is the last paper of my husband. He wrote it in September 1989 and was no more able to prove the manuscript and to add an introduction. Therefore I have tried now to do this for him hoping that the message will be understood.
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GENERATION AND PREDICTION OF SELF-SIMILAR PROCESSES BY SURROGATES
Fractals, 2006A self-similar process has power spectrum with power law depending on its self-similarity parameter H and we use this property for its generation by the method of surrogate data. The surrogates are a set of random data with the same distribution as that of the increments of the process. These are iteratively rearranged according to the rank order of a
Chakraborty, D., Roy, T. K.
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Characterization of Self-Similar Processes with Stationary Increments
Moscow University Mathematics Bulletin, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A remark on self‐similar processes with stationary increments
Canadian Journal of Statistics, 1986AbstractThe upper bound of the parameter of self‐similar processes with stationary increments is given in terms of the moment condition.
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AN INTRODUCTION TO THE THEORY OF SELF-SIMILAR STOCHASTIC PROCESSES
International Journal of Modern Physics B, 2000Self-similar processes such as fractional Brownian motion are stochastic processes that are invariant in distribution under suitable scaling of time and space. These processes can typically be used to model random phenomena with long-range dependence.
EMBRECHTS, PAUL, MAEJIMA, MAKOTO
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Remark on logically constant self-similar processes
Journal of Mathematical Sciences, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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