The Empirical Mode Decomposition and the Hilbert-Huang Transform
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Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:251518
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Segmentation of Killer Whale Vocalizations Using the Hilbert-Huang Transform
The study of cetacean vocalizations is usually based on spectrogram analysis. The feature extraction is obtained from 2D methods like the edge detection algorithm. Difficulties appear when signal-to-noise ratios ...
Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:245936 -
Multimodal Pressure-Flow Analysis: Application of Hilbert Huang Transform in Cerebral Blood Flow Regulation
Quantification of nonlinear interactions between two nonstationary signals presents a computational challenge in different research fields, especially for assessments of physiological systems. Traditional appr...
Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:785243 -
Fast and Adaptive Bidimensional Empirical Mode Decomposition Using Order-Statistics Filter Based Envelope Estimation
A novel approach for bidimensional empirical mode decomposition (BEMD) is proposed in this paper. BEMD decomposes an image into multiple hierarchical components known as bidimensional intrinsic mode functions ...
Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:728356 -
A Fault Diagnosis Approach for Gears Based on IMF AR Model and SVM
An accurate autoregressive (AR) model can reflect the characteristics of a dynamic system based on which the fault feature of gear vibration signal can be extracted without constructing mathematical model and ...
Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:647135 -
Empirical Mode Decomposition Method Based on Wavelet with Translation Invariance
For the mode mixing problem caused by intermittency signal in empirical mode decomposition (EMD), a novel filtering method is proposed in this paper. In this new method, the original data is pretreated by usin...
Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:526038 -
Evaluating Pavement Cracks with Bidimensional Empirical Mode Decomposition
Crack evaluation is essential for effective classification of pavement cracks. Digital images of pavement cracks have been analyzed using techniques such as fuzzy set theory and neural networks. Bidimensional ...
Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:861701 -
Speech Enhancement via EMD
In this study, two new approaches for speech signal noise reduction based on the empirical mode decomposition (EMD) recently introduced by Huang et al. (1998) are proposed. Based on the EMD, both reduction sch...
Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:873204 -
Feature Point Detection Utilizing the Empirical Mode Decomposition
This paper introduces a novel contour-based method for detecting largely affine invariant interest or feature points. In the first step, image edges are detected by morphological operators, followed by edge th...
Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:287061 -
Univariate and Bivariate Empirical Mode Decomposition for Postural Stability Analysis
The aim of this paper was to compare empirical mode decomposition (EMD) and two new extended methods of EMD named complex empirical mode...
Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:657391 -
Single-Trial Classification of Bistable Perception by Integrating Empirical Mode Decomposition, Clustering, and Support Vector Machine
We propose an empirical mode decomposition (EMD-) based method to extract features from the multichannel recordings of local field potential (LFP), collected from the middle temporal (MT) visual cortex in a ma...
Citation: EURASIP Journal on Advances in Signal Processing 2008 2008:592742