Journal ArticleDOI
The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
Norden E. Huang,Zheng Shen,Steven R. Long,Man-Li C. Wu,Hsing H. Shih,Quanan Zheng,Nai-Chyuan Yen,C. C. Tung,Henry H. Liu +8 more
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TLDR
In this paper, a new method for analysing nonlinear and nonstationary data has been developed, which is the key part of the method is the empirical mode decomposition method with which any complicated data set can be decoded.Abstract:
A new method for analysing nonlinear and non-stationary data has been developed. The key part of the method is the empirical mode decomposition method with which any complicated data set can be dec...read more
Citations
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An islanding detection algorithm for distributed generation based on Hilbert–Huang transform and extreme learning machine
TL;DR: In this article, the authors proposed an approach based on Hilbert-Huang transform (HHT) and Extreme learning machine (ELM) to detect an islanding condition in a distribution system with distributed generations (DGs).
Journal ArticleDOI
Specific Emitter Identification Based on Deep Residual Networks
TL;DR: A novel SEI algorithm using deep learning architecture that combines high information integrity with low complexity, which outperforms previous studies in the literature and has the capability of adapting to signals collected under various conditions.
Journal ArticleDOI
Various epileptic seizure detection techniques using biomedical signals: a review.
TL;DR: This review paper is to present state-of-the-art methods and ideas that will lead to valid future research direction in the field of seizure detection as time, frequency, wavelet, empirical mode decomposition and rational function techniques.
Journal ArticleDOI
Quantitative evaluation of orientation-specific damage using elastic waves and probability-based diagnostic imaging
Chao Zhou,Zhongqing Su,Li Cheng +2 more
TL;DR: In this paper, the influence of damage orientation on Lamb wave propagation was quantitatively scrutinised based on the established correlation between damage parameters (location, orientation, shape and size) and extracted signal features, in conjunction with use of an active sensor network in conformity to a pulse-echo configuration.
Journal ArticleDOI
The Application of Hilbert-Huang Transforms to Meteorological Datasets
TL;DR: In this paper, the Hilbert-Huang transform is used to detect synoptic and climatic features from aperiodic and nonlinear signals, such as the passage of extratropical cyclones, fronts and troughs.
References
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TL;DR: In this paper, the authors used the representations of the noise currents given in Section 2.8 to derive some statistical properties of I(t) and its zeros and maxima.
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