Process simulation using randomized Markov chain and truncated marginal distribution

被引:3
作者
Rodionov, AS [1 ]
Choo, H
Youn, HY
机构
[1] Sungkyunkwan Univ, Sch Elect & Comp Engn, Suwon, South Korea
[2] Russian Acad Sci, Suberian Branch, Novosibirsk Inst Computat Math & Math Geophys, Moscow 117901, Russia
关键词
autocorrelation; Newton optimization; random process; randomized Markov chain; simulation;
D O I
10.1023/A:1014358504704
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:69 / 85
页数:17
相关论文
共 17 条
[1]  
[Anonymous], 1979, Monte Carlo Methods, DOI DOI 10.1007/978-94-009-5819-7
[2]   MODELING SPATIALLY CORRELATED K-DISTRIBUTED CLUTTER [J].
ARMSTRONG, BC ;
GRIFFITHS, HD .
ELECTRONICS LETTERS, 1991, 27 (15) :1355-1356
[3]  
Birtwistle G.M., 1973, Simula BEGIN
[4]   NEW METHOD FOR THE SIMULATION OF CORRELATED K-DISTRIBUTED CLUTTER [J].
BLACKNELL, D .
IEE PROCEEDINGS-RADAR SONAR AND NAVIGATION, 1994, 141 (01) :53-58
[5]  
BULGREN WG, 1982, DISCRETE SYSTEM SIMU
[6]  
BUSTOS OH, 1998, P 12 BRAZ S COMP GRA
[7]  
*CACI PROD CO, 1996, MODSIM 3
[8]  
Cox D.R., 1966, The statistical analysis of series of events
[9]  
Dagpunar J., 1988, PRINCIPLES RANDOM VA
[10]  
Feller W., 1971, INTRO PROBABILITY TH