Efficient random process generation for reliable simulation of complex systems

Alexey S. Rodionov; Hyunseung Choo; Hee Yong Youn; Tai M. Chung; Kiheon Park

doi:10.1007/3-540-45718-6_96

Efficient random process generation for reliable simulation of complex systems

Alexey S. Rodionov, Hyunseung Choo, Hee Yong Youn, Tai M. Chung, Kiheon Park

Department of Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Generating pseudo random object is one of the key issues in computer simulation of complex systems. Most earlier systems employ independent and identically distributed random variables, while those of real processes often show nontrivial autocorrelation. In this paper a new approach is presented that generates random process for given marginal distribution and autocorrelation function. The proposed approach achieves significant speed-up and accuracy by using truncated distribution instead of order statistics. An experiment displays more than ten times speed-up for reasonable size system. Moreover, the proposed generator is simple and requires less memory.

Original language	English
Title of host publication	Computational Science – ICCS 2001 - International Conference, Proceedings
Editors	Vassil N. Alexandrov, Jack J. Dongarra, Benjoe A. Juliano, Rene S. Renner, C.J. Kenneth Tan
Publisher	Springer Verlag
Pages	912-921
Number of pages	10
ISBN (Print)	3540422331, 9783540422334
DOIs	https://doi.org/10.1007/3-540-45718-6_96
State	Published - 2001
Event	International Conference on Computational Science, ICCS 2001 - San Francisco, United States Duration: 28 May 2001 → 30 May 2001

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	2074
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Computational Science, ICCS 2001
Country/Territory	United States
City	San Francisco
Period	28/05/01 → 30/05/01

Access to Document

10.1007/3-540-45718-6_96

Cite this

Rodionov, A. S., Choo, H., Youn, H. Y., Chung, T. M., & Park, K. (2001). Efficient random process generation for reliable simulation of complex systems. In V. N. Alexandrov, J. J. Dongarra, B. A. Juliano, R. S. Renner, & C. J. Kenneth Tan (Eds.), Computational Science – ICCS 2001 - International Conference, Proceedings (pp. 912-921). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2074). Springer Verlag. https://doi.org/10.1007/3-540-45718-6_96

Rodionov, Alexey S. ; Choo, Hyunseung ; Youn, Hee Yong et al. / Efficient random process generation for reliable simulation of complex systems. Computational Science – ICCS 2001 - International Conference, Proceedings. editor / Vassil N. Alexandrov ; Jack J. Dongarra ; Benjoe A. Juliano ; Rene S. Renner ; C.J. Kenneth Tan. Springer Verlag, 2001. pp. 912-921 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Efficient random process generation for reliable simulation of complex systems",

abstract = "Generating pseudo random object is one of the key issues in computer simulation of complex systems. Most earlier systems employ independent and identically distributed random variables, while those of real processes often show nontrivial autocorrelation. In this paper a new approach is presented that generates random process for given marginal distribution and autocorrelation function. The proposed approach achieves significant speed-up and accuracy by using truncated distribution instead of order statistics. An experiment displays more than ten times speed-up for reasonable size system. Moreover, the proposed generator is simple and requires less memory.",

author = "Rodionov, \{Alexey S.\} and Hyunseung Choo and Youn, \{Hee Yong\} and Chung, \{Tai M.\} and Kiheon Park",

note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2001.; International Conference on Computational Science, ICCS 2001 ; Conference date: 28-05-2001 Through 30-05-2001",

year = "2001",

doi = "10.1007/3-540-45718-6\_96",

language = "English",

isbn = "3540422331",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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pages = "912--921",

editor = "Alexandrov, \{Vassil N.\} and Dongarra, \{Jack J.\} and Juliano, \{Benjoe A.\} and Renner, \{Rene S.\} and \{Kenneth Tan\}, C.J.",

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Rodionov, AS, Choo, H, Youn, HY, Chung, TM & Park, K 2001, Efficient random process generation for reliable simulation of complex systems. in VN Alexandrov, JJ Dongarra, BA Juliano, RS Renner & CJ Kenneth Tan (eds), Computational Science – ICCS 2001 - International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2074, Springer Verlag, pp. 912-921, International Conference on Computational Science, ICCS 2001, San Francisco, United States, 28/05/01. https://doi.org/10.1007/3-540-45718-6_96

Efficient random process generation for reliable simulation of complex systems. / Rodionov, Alexey S.; Choo, Hyunseung; Youn, Hee Yong et al.
Computational Science – ICCS 2001 - International Conference, Proceedings. ed. / Vassil N. Alexandrov; Jack J. Dongarra; Benjoe A. Juliano; Rene S. Renner; C.J. Kenneth Tan. Springer Verlag, 2001. p. 912-921 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2074).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Efficient random process generation for reliable simulation of complex systems

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AU - Choo, Hyunseung

AU - Youn, Hee Yong

AU - Chung, Tai M.

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N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 2001.

PY - 2001

Y1 - 2001

N2 - Generating pseudo random object is one of the key issues in computer simulation of complex systems. Most earlier systems employ independent and identically distributed random variables, while those of real processes often show nontrivial autocorrelation. In this paper a new approach is presented that generates random process for given marginal distribution and autocorrelation function. The proposed approach achieves significant speed-up and accuracy by using truncated distribution instead of order statistics. An experiment displays more than ten times speed-up for reasonable size system. Moreover, the proposed generator is simple and requires less memory.

AB - Generating pseudo random object is one of the key issues in computer simulation of complex systems. Most earlier systems employ independent and identically distributed random variables, while those of real processes often show nontrivial autocorrelation. In this paper a new approach is presented that generates random process for given marginal distribution and autocorrelation function. The proposed approach achieves significant speed-up and accuracy by using truncated distribution instead of order statistics. An experiment displays more than ten times speed-up for reasonable size system. Moreover, the proposed generator is simple and requires less memory.

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DO - 10.1007/3-540-45718-6_96

M3 - Conference contribution

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SN - 3540422331

SN - 9783540422334

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Computational Science – ICCS 2001 - International Conference, Proceedings

A2 - Alexandrov, Vassil N.

A2 - Dongarra, Jack J.

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Rodionov AS, Choo H, Youn HY, Chung TM, Park K. Efficient random process generation for reliable simulation of complex systems. In Alexandrov VN, Dongarra JJ, Juliano BA, Renner RS, Kenneth Tan CJ, editors, Computational Science – ICCS 2001 - International Conference, Proceedings. Springer Verlag. 2001. p. 912-921. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/3-540-45718-6_96

Efficient random process generation for reliable simulation of complex systems

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