Results 281 to 290 of about 31,823 (308)

Selective Noise Empirical Mode Decomposition

IEEE Signal Processing Letters
We propose selective noise empirical mode decomposition (SNEMD), an adaptive noise-assisted technique that enhances the performance of empirical mode decomposition (EMD) by introducing calibrated complementary noise and selectively extracting optimal modes.
Songhua Liu, Xun Lang, Jiande Wu, Naveed ur Rehman   +3 more
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Hierarchical decomposition based on a variation of empirical mode decomposition

Signal, Image and Video Processing, 2016
Adaptive methods of signal analysis have proved a very useful tool for analysis of non-stationary signals. This is due to the ability of these methods to adapt to the local structures of the signals being analysed, as these methods are not constrained by a fixed basis.
Muhammad Kaleem, Aziz Guergachi, Sridhar Krishnan 0001   +2 more
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BANDWIDTH EMPIRICAL MODE DECOMPOSITION AND ITS APPLICATION

International Journal of Wavelets, Multiresolution and Information Processing, 2008
There are some methods to decompose a signal into different components such as: Fourier decomposition and wavelet decomposition. But they have limitations in some aspects. Recently, there is a new signal decomposition algorithm called the Empirical Mode Decomposition (EMD) Algorithm which provides a powerful tool for adaptive multiscale analysis of ...
Qiwei Xie, Bo Xuan, Silong Peng, Jianping Li 0001, Weixuan Xu, Hua Han 0001   +5 more
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Knife Diagnostics with Empirical Mode Decomposition

2015
This paper deals with the condition monitoring of knives via the Empirical Mode Decomposition (EMD). The cutting process is basically transient, thus Fourier Analysis and similar signal processing tools aren’t optimal because they treat signals as they were periodic. EMD is a signal analysis technique which is particularly suited for non-stationary and/
Cotogno M., Cocconcelli M., Rubini R.
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Empirical Mode Decomposition Analysis for Visual Stylometry

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012
In this paper, we show how the tools of empirical mode decomposition (EMD) analysis can be applied to the problem of “visual stylometry,” generally defined as the development of quantitative tools for the measurement and comparisons of individual style in the visual arts.
James Michael Hughes, Dong Mao, Daniel N. Rockmore, Yang Wang 0020, Qiang Wu 0003   +4 more
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ECG Denoising Based on the Empirical Mode Decomposition

2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006
The electrocardiogram (ECG) has been widely used for diagnosis purposes of heart diseases. Good quality ECG are utilized by the physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts.
Binwei Weng, Manuel Blanco-Velasco, Kenneth E. Barner   +2 more
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Compression by image empirical mode decomposition

IEEE International Conference on Image Processing 2005, 2005
Empirical mode decomposition (EMD) in two dimensions provides a tool for image processing by its special ability to locally separate spatial frequencies. The tendency is that the intrinsic mode functions (IMFs) other than the first are low frequency images. Variable sampling of the EMD is used for image compression. This is done blockwise using the non-
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Multivariate empirical mode decomposition

Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2009
Despite empirical mode decomposition (EMD) becoming a de facto standard for time-frequency analysis of nonlinear and non-stationary signals, its multivariate extensions are only emerging; yet, they are a prerequisite for direct multichannel data analysis.
Rehman, N., Mandic, D. P.
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The complex bidimensional empirical mode decomposition

Signal Processing, 2012
A new method for computing complex bidimensional empirical mode decomposition (BEMD) is presented in this paper. The proposed complex-BEMD uses four quadrant spectra to apply standard BEMD to four real-valued 2D signals. The so-generated intrinsic mode functions (IMFs) are 2D complex-valued, which facilitates the extension of the standard BEMD to the ...
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Reference empirical mode decomposition

2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), 2014
Jiexin Gao, Sahar Javaher Haghighi, Dimitrios Hatzinakos   +2 more
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