Results 251 to 260 of about 858,701 (293)

Intrinsic Fourier Mode Functions

Advances in Data Science and Adaptive Analysis, 2017
In this paper, we study a class of functions that exhibit properties expected from intrinsic mode functions. A type of an empirical instantaneous frequency, depending on the extrema scale, is introduced and its proximity to the classical analytic instantaneous frequency is discussed.
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A CRITERION FOR SELECTING RELEVANT INTRINSIC MODE FUNCTIONS IN EMPIRICAL MODE DECOMPOSITION

Advances in Adaptive Data Analysis, 2010
Information extraction from time series has traditionally been done with Fourier analysis, which use stationary sines and cosines as basis functions. However, data that come from most natural phenomena are mostly nonstationary. A totally adaptive alternative method has been developed called the Hilbert–Huang transform (HHT), which involves generating ...
Albert Y. Ayenu-Prah, Nii O. Attoh-Okine
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CONSTRUCTING CROSSOVER-FRACTALS USING INTRINSIC MODE FUNCTIONS

Advances in Adaptive Data Analysis, 2010
Real nonstationary time sequences are in general not monofractals. That is, they cannot be characterized by a single value of fractal dimension. It has been shown that many real-time sequences are crossover-fractals: sequences with two fractal dimensions — one for the short and the other for long ranges.
Sy-Sang Liaw, Feng-Yuan Chiu
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Decomposition of functions into pairs of intrinsic mode functions

Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2008
The intrinsic mode functions (IMFs) arise as basic modes from the application of the empirical mode decomposition (EMD) to functions or signals. In this procedure, instantaneous frequencies are subsequently extracted from the IMFs by the simple application of the Hilbert transform, thereby providing a multiscale analysis of the signal's ...
Vatchev, Vesselin, Sharpley, Robert
exaly   +3 more sources

Hyperspectral Image Classification Using Denoising of Intrinsic Mode Functions

IEEE Geoscience and Remote Sensing Letters, 2011
This letter proposes the use of denoising in conjunction with 2-D empirical mode decomposition (2D-EMD) of hyperspectral image bands for higher classification accuracy. Initially, 2D-EMD is performed to hyperspectral image bands for decomposition into intrinsic mode functions (IMFs). Then, denoising is applied to the first IMF of each band because this
Begüm Demir, Sarp Ertürk, M. Kemal Güllü   +2 more
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INTRINSIC MODE FUNCTIONS OF EARTHQUAKE SLIP DISTRIBUTION

Advances in Adaptive Data Analysis, 2010
In this paper, empirical mode decomposition technique is used to analyze the spatial slip distribution of five past earthquakes. It is shown that the finite fault slip models exhibit five empirical modes of oscillation. The last intrinsic mode is positive and characterizes the non-stationary mean of the slip distribution.
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The structures of some typical intrinsic mode functions

Mathematical Methods in the Applied Sciences, 2012
The empirical mode decomposition is a powerful tool for analyzing nonlinear and nonstationary data. In this method, one of the main conceptual innovations is the introduction of intrinsic mode functions (IMFs), which arise as basic modes from the application of the empirical mode decomposition to signals.
Yang, Zhijing, Yang, Lihua
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Noise-assisted intrinsic mode function coherence in seizure anticipation

2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011
Epilepsy is a common neurological disorder characterized by recurrent electrophysiological activities, known as seizures. We explore the applicability of noise-assisted Ensemble Empirical Mode Decomposition (EEMD) for patient-specific seizure anticipation.
Daniel W. Moller, Alan W. L. Chiu
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An intrinsic mode function basis dictionary for auditory signal processing

2014 International Conference on Audio, Language and Image Processing, 2014
As one important field of sparse representation, the research of dictionary learning attracts most researchers interest in signal processing study. Empirical Mode Decomposition (EMD), as an efficient and adaptive signal decomposition method that depends completely on the signal, is considered as an innovative and appropriative the basis function theory.
Chang Gao, Haifeng Li 0001, Lin Ma 0003
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Two-Dimensional Curvature-Based Analysis of Intrinsic Mode Functions

IEEE Signal Processing Letters, 2018
A novel approach in modeling the empirical mode decomposition (EMD) is proposed here, allowing a perfect image recovery and, for instance, a straightforward extension for multidimensional $\mathbb{R}^{n}$ signals. In fact, thanks to a new sifting process modeling, where the two-dimensional (2-D) local mean envelope is formulated with the ...
El-Hadji Samba Diop, Radjesvarane Alexandre, Abdel-Ouahab Boudraa   +2 more
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