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Proceedings Paper

A plea for adaptive data analysis
Author(s): Norden E. Huang
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Paper Abstract

The existing methods of data analysis, either the probability theory or the spectral analysis, are all developed by mathematicians or based on their rigorous mathematical rules. For data analysis, we have to face the reality of nonstationarity and nonlinearity in the data. Hilbert-Huang Transform (HHT) is the designated name for the result of Empirical Mode Decomposition (EMD) and the Hilbert Spectral Analysis (HSA) methods, which were both introduced recently by Huang et al. (1996, 1998, 1999 and 2003). The method is adaptive, and specifically for analyzing data from nonlinear and nonstationary processes.

Paper Details

Date Published: 9 April 2007
PDF: 6 pages
Proc. SPIE 6576, Independent Component Analyses, Wavelets, Unsupervised Nano-Biomimetic Sensors, and Neural Networks V, 65760P (9 April 2007); doi: 10.1117/12.725199
Show Author Affiliations
Norden E. Huang, National Central Univ. (Taiwan)


Published in SPIE Proceedings Vol. 6576:
Independent Component Analyses, Wavelets, Unsupervised Nano-Biomimetic Sensors, and Neural Networks V
Harold H. Szu; Jack Agee, Editor(s)

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