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Abstract: f noise and statistically self-similar processes such as fractional Brownian motion (fBm) are vital for modeling numerous real-world phenomena, from network traffic to DNA to the stock market. Although several algorithms exist for synthesizing discrete-time samples of a 1=f process, these algorithms are inexact, meaning that the covariance of the synthesized processes can deviate significantly from that of a true 1=f process. However, the Fast Fourier Transform (FFT) can be used to exactly ... (Update)
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BibTeX entry: (Update)
@misc{ matthew-fast,
author = "Long-Range-Dependent Processes Matthew",
title = "Fast, Exact Synthesis of Gaussian and nonGaussian",
url = "citeseer.ist.psu.edu/767449.html" }
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