On the aggregation of self-similar processes

Gianluca Mazzini, Riccardo Rovatti, Gianluca Setti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


The problem of aggregating different stochastic process into a unique one that must be characterized based on the statistical knowledge of its components is a key point in the modeling of many complex phenomena such as the merging of traffic flows at network nodes. Depending on the physical intuition on the interaction between the processes, many different aggregation policies can be devised, from averaging to taking the maximum in each time slot. We here address flows averaging and maximum since they are very common modeling options. Then we give a set of axioms defining a general aggregation operator and, based on some advanced results of functional analysis, we investigate how the decay of correlation of the original processes affect the decay of correlation (and thus the self-similar features) of the aggregated process. Copyright © 2005 The Institute of Electronics, Information and Communication Engineers.
Original languageEnglish (US)
Title of host publicationIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
PublisherInstitute of Electronics, Information and Communication, Engineers, IEICE
Number of pages7
StatePublished - Jan 1 2005
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-02-15


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