Fractional exponential model for fractal point processes

E. Moulines; R. Soulier

Fractional exponential model for fractal point processes

E. Moulines
, R. Soulier

Telecom Paris

Résultats de recherche: Contribution à un journal › Article de conférence › Revue par des pairs

1 Citation (Scopus)

Résumé

Markov-Modulated Poisson process has long been used to model arrivals at networks. Recent work has shown that such models may be inadequate because traffic on networks may exhibit self-similar (or fractal) behavior. The analysis of fractal point processes is thus of crucial importance. In this contribution, a novel analysis technique is presented, based on log-periodogram regression and fractional exponential models. A procedure, derived from the Mallows's C_p statistics is proposed to choose the regression order. Results are presented on both simulated and real data.

langue originale	Anglais
Pages (de - à)	1107-1111
Nombre de pages	5
journal	Conference Record of the Asilomar Conference on Signals, Systems and Computers
Volume	2
état	Publié - 1 janv. 1998
Evénement	Proceedings of the 1997 31st Asilomar Conference on Signals, Systems & Computers. Part 1 (of 2) - Pacific Grove, CA, USA Durée: 2 nov. 1997 → 5 nov. 1997

Contient cette citation

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title = "Fractional exponential model for fractal point processes",

abstract = "Markov-Modulated Poisson process has long been used to model arrivals at networks. Recent work has shown that such models may be inadequate because traffic on networks may exhibit self-similar (or fractal) behavior. The analysis of fractal point processes is thus of crucial importance. In this contribution, a novel analysis technique is presented, based on log-periodogram regression and fractional exponential models. A procedure, derived from the Mallows's Cp statistics is proposed to choose the regression order. Results are presented on both simulated and real data.",

author = "E. Moulines and R. Soulier",

year = "1998",

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day = "1",

language = "English",

volume = "2",

pages = "1107--1111",

journal = "Conference Record of the Asilomar Conference on Signals, Systems and Computers",

issn = "1058-6393",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "Proceedings of the 1997 31st Asilomar Conference on Signals, Systems \& Computers. Part 1 (of 2) ; Conference date: 02-11-1997 Through 05-11-1997",

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T1 - Fractional exponential model for fractal point processes

AU - Moulines, E.

AU - Soulier, R.

PY - 1998/1/1

Y1 - 1998/1/1

N2 - Markov-Modulated Poisson process has long been used to model arrivals at networks. Recent work has shown that such models may be inadequate because traffic on networks may exhibit self-similar (or fractal) behavior. The analysis of fractal point processes is thus of crucial importance. In this contribution, a novel analysis technique is presented, based on log-periodogram regression and fractional exponential models. A procedure, derived from the Mallows's Cp statistics is proposed to choose the regression order. Results are presented on both simulated and real data.

AB - Markov-Modulated Poisson process has long been used to model arrivals at networks. Recent work has shown that such models may be inadequate because traffic on networks may exhibit self-similar (or fractal) behavior. The analysis of fractal point processes is thus of crucial importance. In this contribution, a novel analysis technique is presented, based on log-periodogram regression and fractional exponential models. A procedure, derived from the Mallows's Cp statistics is proposed to choose the regression order. Results are presented on both simulated and real data.

M3 - Conference article

AN - SCOPUS:0031649446

SN - 1058-6393

VL - 2

SP - 1107

EP - 1111

JO - Conference Record of the Asilomar Conference on Signals, Systems and Computers

JF - Conference Record of the Asilomar Conference on Signals, Systems and Computers

T2 - Proceedings of the 1997 31st Asilomar Conference on Signals, Systems & Computers. Part 1 (of 2)

Y2 - 2 November 1997 through 5 November 1997

ER -

Fractional exponential model for fractal point processes

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