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공공누리This item is licensed Korea Open Government License

Title
A Study on Transformation of Self-Simialr Processes with Arbitrary Marginal Distributions
Author(s)
H.Jeong이종숙
Publication Year
2006-09-30
Abstract
Stochastic discrete-event simulation studies of communication networks often require a mechanism to transform self-similar processes with normal marginal distributions into self-similar processes with arbitrary marginal distributions. The problem of generating a self-similar process of a given marginal distribution and an autocorrelation structure is difficult and has not been fully solved. Our results presented in this paper provide clear experimental evidence that the autocorrelation function of the input process is not preserved in the output process generated by the inverse cumulative distribution function (ICDF) transformation, where the output process has an infinite variance. On the other hand, it preserves autocorrelation functions of the input process where the output marginal distributions and the ICDF transformation is applied to long-range dependent self-similar processes with normal marginal distributions.
Keyword
Self-similar process; Stochastic simulation
Journal Title
Lecture Notes of Computer Science(LNCS)
Citation Volume
4186
ISSN
0302-9743
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Appears in Collections:
7. KISTI 연구성과 > 학술지 발표논문
URI
https://repository.kisti.re.kr/handle/10580/13621
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