Norden E. Huang

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, doi: 10.1098/rspa.1998.0193 454 1998 Proc. R. Soc. Lond. A Yen, Chi Chao Tung and Henry H. Liu Norden E. Huang, Zheng Shen, Steven R. Long, Manli C. Wu, Hsing H. Shih, Quanan Zheng, Nai-Chyuan nonlinear and non-stationary time series analysis The empirical mode decomposition and the Hilbert spectrum for References(More)
A new Ensemble Empirical Mode Decomposition (EEMD) is presented. This new approach consists of sifting an ensemble of white noise-added signal (data) and treats the mean as the final true result. Finite, not infinitesimal, amplitude white noise is necessary to force the ensemble to exhaust all possible solutions in the sifting process, thus making the(More)
We survey the newly developed Hilbert spectral analysis method and its applications to Stokes waves, nonlinear wave evolution processes, the spectral form of the random wave field, and turbulence. Our emphasis is on the inadequacy of presently available methods in nonlinear and nonstationary data analysis. Hilbert spectral analysis is here proposed as an(More)
By Norden E. Huang1, Man-L i C. W u2, Steven R. Long3, Samuel S. P. Shen4, Wendong Q u5, Per Gloersen1 and Kuang L. Fan6 1Code 971, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA (norden.e.huang@nasa.gov) 2Code 910, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA 3Code 972, NASA GSFC/Wallops Flight Facility, Wallops Island, VA 23337,(More)
Determining trend and implementing detrending operations are important steps in data analysis. Yet there is no precise definition of "trend" nor any logical algorithm for extracting it. As a result, various ad hoc extrinsic methods have been used to determine trend and to facilitate a detrending operation. In this article, a simple and logical definition of(More)
Instantaneous frequency (IF) is necessary for understanding the detailed mechanisms for nonlinear and nonstationary processes. Historically, IF was computed from analytic signal (AS) through the Hilbert transform. This paper offers an overview of the difficulties involved in using AS, and two new methods to overcome the difficulties for computing IF. The(More)
Dengue fever is a mosquito-borne virus that infects 50-100 million people each year. Of these infections, 200,000-500,000 occur as the severe, life-threatening form of the disease, dengue haemorrhagic fever (DHF). Large, unanticipated epidemics of DHF often overwhelm health systems. An understanding of the spatial-temporal pattern of DHF incidence would aid(More)
[1] Data analysis has been one of the core activities in scientific research, but limited by the availability of analysis methods in the past, data analysis was often relegated to data processing. To accommodate the variety of data generated by nonlinear and nonstationary processes in nature, the analysis method would have to be adaptive. Hilbert-Huang(More)
Pathologic states are associated with a loss of dynamical complexity. Therefore, therapeutic interventions that increase physiologic complexity may enhance health status. Using multiscale entropy analysis, we show that the postural sway dynamics of healthy young and healthy elderly subjects are more complex than that of elderly subjects with a history of(More)
A multi-dimensional ensemble empirical mode decomposition (MEEMD) for multidimensional data (such as images or solid with variable density) is proposed here. The decomposition is based on the applications of ensemble empirical mode decomposition (EEMD) to slices of data in each and every dimension involved. The final reconstruction of the corresponding(More)