Paper Title:
Detection of Fractional Data Based on Hilbert-Huang Transformation
  Abstract

In many theoretical analysis and engineering application fields, fractional Brownian motions has proposed to be a valuable random excitation due to its' key self-similarity and fractal nature. And Hilbert-Huang transformation is counted as an effective tool to deal with nonlinear and non-stationary data. In this paper, we propose Hilbert-Huang transformation to process fractional data, then by verifying and differentiating the marginal spectrum or power spectrum of fractional data we formulate a stochastic detection scheme.

  Info
Periodical
Advanced Materials Research (Volumes 308-310)
Chapter
Reverse Engineering
Edited by
Jian Gao
Pages
1546-1550
DOI
10.4028/www.scientific.net/AMR.308-310.1546
Citation
C. J. Li, J. P. Wan, "Detection of Fractional Data Based on Hilbert-Huang Transformation", Advanced Materials Research, Vols. 308-310, pp. 1546-1550, 2011
Online since
August 2011
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Price
$32.00
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