A correlation-based computational model for synthesizing long-range dependent data

被引：37

作者：

Li, M ^{[1
]}

Chi, CH

机构：

[1] Natl Univ Singapore, Sch Comp, Dept Comp Sci, Singapore 117543, Singapore

[2] So Yangtze Univ, Sch Informat Engn, Wuxi, Peoples R China

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2003年 / 340卷 / 6-7期

关键词：

long-range dependent data generation; Brownian motion; fractional Gaussian noise; filters; Fourier analysis; teletraffic;

D O I：

10.1016/j.jfranklin.2003.09.002

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The authors present a computation model to generate long-range dependent (LRD) data according to a given correlation structure by filtering white noise. The simulation procedure of LRD data according to a given correlation structure is explained. A case study is illustrated with real LRD data series in the Internet. (C) 2003 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

引用

页码：503 / 514

页数：12

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