Process Simulation Using Randomized Markov Chain and Truncated Marginal Distribution

Authors:
Alexei S. Rodionov;Hyunseung Choo;Hee Y. Youn
Affiliations:
School of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Korea alrod@ece.skku.ac.kr;School of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Korea choo@ece.skku.ac.kr;School of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Korea youn@ece.skku.ac.kr
Venue:
The Journal of Supercomputing - Special issue on computational issues in fluid dynamics optimization and simulation
Year:
2002

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Abstract

Generating pseudo random objects is one of the key issues in computer simulation of complex systems. Most earlier simulation systems include procedures for the generation of independent and identically distributed random variables or some classical random processes, such as white noise. In this paper we propose a new approach to the generation of wide ranges of processes that are characterized by marginal distribution and autocorrelation function that are significant in many cases. The proposed algorithm is based on the use of truncated distribution that gives more simplicity and efficiency in comparison with the previous one. The effectiveness of the proposed algorithm is verified using computer simulation of various real examples.