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ICASSP
2011
IEEE
12 years 8 months ago
Multichannel EEG analysis based on multi-scale multi-information
Functional connectivity has been widely used to reveal the dependencies between signals in complex networks such as neural networks observed from electroencephalogram (EEG) data. ...
Ying Liu, Selin Aviyente
ICASSP
2011
IEEE
12 years 8 months ago
Signal extrapolation using Empirical Mode Decomposition with financial applications
In order to extrapolate a signal, Empirical Mode Decomposition is used to decompose it into simpler components. Each component is individually extrapolated linearly, and the fina...
Nikolaos Tsakalozos, Konstantinos Drakakis, Scott ...
ICASSP
2011
IEEE
12 years 8 months ago
A complete ensemble empirical mode decomposition with adaptive noise
In this paper an algorithm based on the ensemble empirical mode decomposition (EEMD) is presented. The key idea on the EEMD relies on averaging the modes obtained by EMD applied t...
María Eugenia Torres, Marcelo A. Colominas,...
ICASSP
2009
IEEE
13 years 2 months ago
Qualitative analysis of rotational modes within three dimensional empirical mode decomposition
An analysis of quaternion-valued intrinsic mode functions (IMFs) within three dimensional empirical mode decomposition is presented. This is achieved by using the delay vector var...
Naveed ur Rehman, Danilo P. Mandic
COST
2009
Springer
176views Multimedia» more  COST 2009»
13 years 8 months ago
Pathological Voice Analysis and Classification Based on Empirical Mode Decomposition
Empirical mode decomposition (EMD) is an algorithm for signal analysis recently introduced by Huang. It is a completely datadriven non-linear method for the decomposition of a sign...
Gastón Schlotthauer, María Eugenia T...
ITNG
2010
IEEE
13 years 9 months ago
A Forecasting Capability Study of Empirical Mode Decomposition for the Arrival Time of a Parallel Batch System
This paper demonstrates the feasibility and potential of applying empirical mode decomposition (EMD) to forecast the arrival time behaviors in a parallel batch system. An analysis...
Linh Ngo, Amy W. Apon, Doug Hoffman
ICASSP
2008
IEEE
13 years 10 months ago
Some properties of an empirical mode type signal decomposition algorithm
The empirical mode decomposition (EMD) has seen widespread use for analysis of nonlinear and nonstationary time-series. Despite some practical success, it lacks a firm theoretica...
Stephen D. Hawley, Les E. Atlas, Howard J. Chizeck
SCALESPACE
2009
Springer
13 years 10 months ago
Computational Geometry-Based Scale-Space and Modal Image Decomposition
In this paper a framework for defining scale-spaces, based on the computational geometry concepts of α-shapes, is proposed. In this approach, objects (curves or surfaces) of incr...
Anatole Chessel, Bertrand Cinquin, Sabine Bardin, ...
ICASSP
2009
IEEE
13 years 11 months ago
A PDE characterization of the intrinsic mode functions
For the first time, a proof of the sifting process (SP) and so the empirical mode decomposition (EMD), is given. For doing this, lower and upper envelopes are modeled in a more c...
El-Hadji Samba Diop, R. Alexandre, Abdel-Ouahab Bo...
ICPR
2008
IEEE
14 years 5 months ago
Extending depth of field by intrinsic mode image fusion
Here, a versatile data-driven application independent method to extend the depth of field is presented. The principal contribution in this effort is the use of features extracted ...
Andreas Koschan, Harishwaran Hariharan, Mongi A. A...