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Multivariate Empirical Mode Decomposition analysis of Swarm data [PDF]
Il Nuovo Cimento C, 2018 The magnetosphere and the ionosphere of the Earth are populated by different current systems with well-structured spatial patterns. In this paper, by using low-resolution (1 Hz) Swarm A data, we present an application of the Multivariate Empirical Mode ...
Alberti, T.
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Multivariate empirical mode decomposition
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2009Despite 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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Filter Bank Property of Multivariate Empirical Mode Decomposition
IEEE Transactions on Signal Processing, 2011The multivariate empirical mode decomposition (MEMD) algorithm has been recently proposed in order to make empirical mode decomposition (EMD) suitable for processing of multichannel signals. To shed further light on its performance, we analyze the behavior of MEMD in the presence of white Gaussian noise.
Naveed ur Rehman, Danilo P. Mandic
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FPGA-Based Design for Online Computation of Multivariate Empirical Mode Decomposition
IEEE Transactions on Circuits and Systems I: Regular Papers, 2020Multivariate or multichannel data have become ubiquitous in many modern scientific and engineering applications, e.g., biomedical engineering, owing to recent advances in sensor and computing technology. Processing these data sets is challenging owing to their large size and multidimensional nature, thus requiring specialized algorithms and efficient ...
Sikender Gull +2 more
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A joint framework for multivariate signal denoising using multivariate empirical mode decomposition
Signal Processing, 2017In this paper, a novel multivariate denoising scheme using multivariate empirical mode decomposition (MEMD) is proposed. Unlike previous EMD-based denoising methods, the proposed scheme can align common frequency modes across multiple channels of a multivariate data, thus, facilitating direct multichannel data denoising. The key idea in this work is to
Huan Hao, Huali Wang, Naveed ur Rehman
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Fast and Adaptive Empirical Mode Decomposition for Multidimensional, Multivariate Signals
IEEE Signal Processing Letters, 2018Over the last decade, empirical mode decomposition (EMD) has developed into a versatile tool for adaptive, scale-based modal decomposition. EMD has proven to be capable of decomposing multivariate signals with cross-channel mode alignment. However, the algorithms for envelope identification in multivariate EMD come with a computational burden rendering
Mruthun R. Thirumalaisamy +1 more
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2019 27th Signal Processing and Communications Applications Conference (SIU), 2019
EEG signals are frequently used to record seizures of epilepsy. However, observation of these seizures is difficult and time-consuming. Fourier-based approaches are not suitable for the nonlinear and nonstationary nature of EEG. For this reason, empirical methods such as multivariate empirical mode decomposition (MEMD) are used in the analysis of ...
Barkin Büyükçakir, Ali Yener Mutlu
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EEG signals are frequently used to record seizures of epilepsy. However, observation of these seizures is difficult and time-consuming. Fourier-based approaches are not suitable for the nonlinear and nonstationary nature of EEG. For this reason, empirical methods such as multivariate empirical mode decomposition (MEMD) are used in the analysis of ...
Barkin Büyükçakir, Ali Yener Mutlu
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2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2023
Fatigue-induced physiological tremor (FIPT) is undesirable when performing micromanipulation tasks that require high precision. It is important to characterise this form of tremor to aid in identifying and suppressing it from the intended micromanipulation task. Researchers have used surface electromyography (sEMG) and mechanomyography (MMG) separately
Poongavanam Palani +2 more
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Fatigue-induced physiological tremor (FIPT) is undesirable when performing micromanipulation tasks that require high precision. It is important to characterise this form of tremor to aid in identifying and suppressing it from the intended micromanipulation task. Researchers have used surface electromyography (sEMG) and mechanomyography (MMG) separately
Poongavanam Palani +2 more
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Application of multivariate empirical mode decomposition for seizure detection in EEG signals
2010 Annual International Conference of the IEEE Engineering in Medicine and Biology, 2010We present a method for the analysis of electroencephalogram (EEG) signals which has the potential to distinguish between ictal and seizure-free intracranial EEG recordings. This is achieved by analyzing common frequency components in multichannel EEG recordings, using the multivariate empirical mode decomposition (MEMD) algorithm.
Naveed, Ur Rehman +2 more
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Multivariate empirical mode decomposition approach for adaptive denoising of fringe patterns
Optics Letters, 2012An adaptive approach is presented for noise reduction of optical fringe patterns using multivariate empirical mode decomposition. Adjacent rows and columns of patterns are treated as multichannel signals and are decomposed into multiscale components.
Xiang, Zhou +3 more
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