Abstract:
This paper describes an approximate method for synthesizing sequences of statistically self-similar processes and analyses its performance to generate sample sequences wi...View moreMetadata
Abstract:
This paper describes an approximate method for synthesizing sequences of statistically self-similar processes and analyses its performance to generate sample sequences with long-range dependence. The method is based upon approximating the infinite dimensional difference equation which describes the FARIMA(0,α,0) model by a finite dimensional difference equation. The parameters estimation for parameterizing the binomial coefficients is performed by deterministic signal modeling techniques (Prony, Shanks and Steiglitz MAcBride). In addition to allow considerable savings in memory requirements and great reduction in computation time, the performance analysis results show that the generated sequences are statistically self-similar in the sense that the estimated Hurst parameter is very close to that imposed in the sequences generator.
Published in: 2009 16th IEEE International Conference on Electronics, Circuits and Systems - (ICECS 2009)
Date of Conference: 13-16 December 2009
Date Added to IEEE Xplore: 17 February 2010
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