MCM08c

Mehran Talebinejad, Adrian D. C. Chan, Ali Miri. Spectrum-Based Fractal Analysis Using Piecewise Statistically Self-Affine Power Laws. In Proceedings of the 31st Canadian Medical and Biological Engineering Conference (CMBEC 2008), Montreal, Canada, June 2008.

Abstract

In this paper we present a novel set of statistically selfaffine power laws and an algorithm for parameter estimation of a piecewise power law combination. The piecewise combination is applicable to irregular power spectral densities which do not follow the classic form of strict statistical self-affinity. The piecewise modeling also enables local analysis with variable magnificationfactors, which is very informative about the spectral distribution of the texture. Results of an experiment on simulated myoelectricsignals are also presented. In this experiment, two conditions in which a single power law results in large errors are investigated. The results show that extension of the modeling to a piecewisecombinational approach improves the accuracy and results in a better representation of the power spectrum. The results also show a great potential for applications of this approach to a wide variety of bio-signals with a multi-fractal behavior, which is very close to combinational mono-fractals in texture

Contact

Mehran Talebinejad
Adrian D. C. Chan
Ali Miri

BibTex Reference

@InProceedings{MCM08c,
   Author = {Talebinejad, Mehran and D. C. Chan, Adrian and Miri, Ali},
   Title = {Spectrum-Based Fractal Analysis Using Piecewise Statistically Self-Affine Power Laws},
   BookTitle = {Proceedings of the 31st Canadian Medical and Biological Engineering Conference (CMBEC 2008)},
   Address = {Montreal, Canada},
   Month = {June},
   Year = {2008}
}

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