Results 1 to 10 of about 324 (113)

Matlab Open Source Code: Noise-Assisted Multivariate Empirical Mode Decomposition Based Causal Decomposition for Causality Inference of Bivariate Time Series [PDF]

Frontiers in Neuroinformatics, 2022
Causality inference has arrested much attention in academic studies. Currently, multiple methods such as Granger causality, Convergent Cross Mapping (CCM), and Noise-assisted Multivariate Empirical Mode Decomposition (NA-MEMD) are introduced to solve the
Yi Zhang, Yi Zhang, Yi Zhang, Guan Wang, Ziwen Li, Mingjun Xie, Branko Celler, Steven Su, Peng Xu, Peng Xu, Dezhong Yao, Dezhong Yao   +11 more
doaj   +2 more sources

Fast Multivariate Empirical Mode Decomposition

IEEE Access, 2018
The multivariate empirical mode decomposition (MEMD) has been pioneered recently for adaptively processing of multichannel data. Despite its high efficiency on time-frequency analysis of nonlinear and nonstationary signals, high computational load and ...
Xun Lang, Qian Zheng, Zhiming Zhang, Shan Lu, Lei Xie, Alexander Horch, Hongye Su   +6 more
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Multiscale Traffic Dynamics Representation for Forecasting via MEMD-Guided Dual-Branch Recurrent Networks [PDF]

Sensors
Traffic flow forecasting remains challenging because raw traffic flow observations often contain mixed temporal patterns, including slowly varying trends and fast local fluctuations.
Yichen Qian, Taiming Kang, Shengduo Zhang, Chaoneng Li, Xiaolong Wang, Shuxu Zhao   +5 more
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GPU-Accelerated Multivariate Empirical Mode Decomposition for Massive Neural Data Processing

IEEE Access, 2017
This paper presents an efficient implementation of multivariate empirical mode decomposition (MEMD) algorithm, a multivariate extension of EMD algorithm.
Taha Mujahid, Anis Ur Rahman, Muhammad Murtaza Khan   +2 more
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Mode decomposition-based time-varying phase synchronization for fMRI [PDF]

NeuroImage, 2022
Recently, there has been significant interest in measuring time-varying functional connectivity (TVC) between different brain regions using resting-state functional magnetic resonance imaging (rs-fMRI) data.
Hamed Honari, Martin A. Lindquist
doaj   +2 more sources

Ground Roll Attenuation of Multicomponent Seismic Data with the Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD) Method

Applied Sciences, 2022
Multicomponent seismic exploration provides more wavefield information for imaging complex subsurface structures and predicting reservoirs. Ground roll is strongly coherent noise in land multicomponent seismic data and exhibits similar features, which ...
Liying Xiao, Zhifu Zhang, Jianjun Gao
doaj   +3 more sources

Bidimensional Multivariate Empirical Mode Decomposition With Applications in Multi-Scale Image Fusion

IEEE Access, 2019
Empirical mode decomposition (EMD) is a fully data-driven technique designed for multi-scale decomposition of signals into their natural scale components, called intrinsic mode functions (IMFs).
Yili Xia, Bin Zhang, Wenjiang Pei, Danilo P. Mandic   +3 more
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Multivariate Nonlinear Sparse Mode Decomposition and Its Application in Gear Fault Diagnosis

IEEE Access, 2021
Multi-channel signal has more abundant and accurate state characteristic information than single channel signal. How to separate fault characteristic information from the multi-channel signal is the key of fault diagnosis.
Haiyang Pan, Wanwan Jiang, Qingyun Liu, Jinde Zheng   +3 more
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Hyperparameter optimization of support vector machine using adaptive differential evolution for electricity load forecasting

Energy Reports, 2022
Peak load forecasting plays an integral part in the planning and operating of energy plants for the utility companies and policymakers to devise reliable and stable power infrastructure.
M. Zulfiqar, M. Kamran, M.B. Rasheed, T. Alquthami, A.H. Milyani   +4 more
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A Method for Blind Source Separation of Multichannel Electromagnetic Radiation in the Field

IEEE Access, 2020
Considering the multichannel instability, spectral overlap and strong interference of electromagnetic radiation signals in the integrated electric propulsion systems of ships, a new method is proposed which combines multivariate empirical mode ...
Sheng Liu, Bangmin Wang, Lanyong Zhang
doaj   +1 more source