Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.jfranklin.2003.09.002
Title: A correlation-based computational model for synthesizing long-range dependent data
Authors: Li, M. 
Chi, C.-H. 
Keywords: Brownian motion
Filters
Fourier analysis
Fractional Gaussian noise
Long-range dependent data generation
Teletraffic
Issue Date: 2004
Source: Li, M., Chi, C.-H. (2004). A correlation-based computational model for synthesizing long-range dependent data. Journal of the Franklin Institute 340 (6-7) : 503-514. ScholarBank@NUS Repository. https://doi.org/10.1016/j.jfranklin.2003.09.002
Abstract: 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. © 2003 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Source Title: Journal of the Franklin Institute
URI: http://scholarbank.nus.edu.sg/handle/10635/39584
ISSN: 00160032
DOI: 10.1016/j.jfranklin.2003.09.002
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