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Two-Dimensional Variational Mode Decomposition
2015In this paper we propose a variational method to adaptively decompose an image into few different modes of separate spectral bands, which are unknown before. A popular method for recursive one dimensional signal decomposition is the Empirical Mode Decomposition algorithm, introduced by Huang in the nineties. This algorithm, as well as its 2D extension,
Konstantin Dragomiretskiy +1 more
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A queued Variational Mode Decomposition method
Journal of the Franklin InstitutezbMATH Open Web Interface contents unavailable due to conflicting licenses.
Wei Chen, Yong Zhang 0018
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Nonlinear Chirp Mode Decomposition: A Variational Method
IEEE Transactions on Signal Processing, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chen, Shiqian +4 more
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2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2016
Most of the non-stationary signals need adaptive processing technique for denoising, signal processing for feature extraction and analysis. In this regard, signal decomposition methods plays a vital role as selective reconstruction extracts the enhanced version of the signal buried in the noise.
Uday Maji, Saurabh Pal 0003
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Most of the non-stationary signals need adaptive processing technique for denoising, signal processing for feature extraction and analysis. In this regard, signal decomposition methods plays a vital role as selective reconstruction extracts the enhanced version of the signal buried in the noise.
Uday Maji, Saurabh Pal 0003
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Denoising of phonocardiogram signals using variational mode decomposition
2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2017Recent advances in signal processing and the revolution by the mobile technologies have spurred several innovations in all the areas and albeit more so in home based tele-medicine. We used variational mode decomposition (VMD) based denoising on large-scale phonocardiogram (PCG) data sets and achieved better accuracy. We have also implemented a reliable,
V. G. Sujadevi +4 more
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Variational mode decomposition for ultrasound computed tomography
Medical Imaging 2020: Ultrasonic Imaging and Tomography, 2020In recent years, Ultrasound computed tomography (USCT) has important clinical application prospect in breast cancer screening and early diagnosis. In this paper, the biomedical image denoising technique based on variational mode decomposition (VMD) method for USCT is investigated.
Shanshan Wang +5 more
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Variational mode decomposition denoising combined with the Hausdorff distance
Review of Scientific Instruments, 2017Variational mode decomposition (VMD) is a recently introduced adaptive signal decomposition algorithm with a solid theoretical foundation and good noise robustness compared with empirical mode decomposition (EMD). However, there is still a problem with this algorithm associated with the selection of relevant modes.
Wenping Ma +3 more
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Complex Variational Mode Decomposition for Slop-Preserving Denoising
IEEE Transactions on Geoscience and Remote Sensing, 2018We have introduced a new decomposition method for seismic data, termed complex variational mode decomposition (VMD), and we have also designed a new filtering technique for random noise attenuation in seismic data by applying the VMD on constant-frequency slices in the frequency–offset ( $f$ – $x$ ) domain.
Siwei Yu 0002, Jianwei Ma
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Detection of voltage variation events using variational mode decomposition
2017 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), 2017This paper presents a method of detecting voltage sag, swell and interruption events based on a signal processing tool viz. variational mode decomposition (VMD). The proposed method is able to keep track of variations in amplitude, phase, frequency and undelivered energy due to such events.
Pankaj D. Achlerkar +2 more
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Image dehazing using variational mode decomposition
2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), 2017Haze is caused by the scattering of airtight in atmosphere and it deteriorates the contrast of the photographs. Here, we propose a novel approach for haze removal based on Two Dimensional Variational Mode Decomposition (2D VMD). Two dimensional VMD decomposes the input image into desired number of bands with different central frequencies. From this set
Hima T. Suseelan, V. Sowmya, K. P. Soman
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