Filters








676 Hits in 7.0 sec

Multivariate empirical mode decomposition and application to multichannel filtering

Julien Fleureau, Amar Kachenoura, Laurent Albera, Jean-Claude Nunes, Lotfi Senhadji
2011 Signal Processing  
Empirical Mode Decomposition (EMD) is an emerging topic in signal processing research, applied in various practical fields due in particular to its data-driven filter bank properties.  ...  Besides, we show that X-EMD extends the filter bank properties enjoyed by monovariate EMD to the case of multivariate EMD.  ...  Filter bank structure and application to multichannel sleep recording One important property of the classical monovariate EMD [1] especially highlighted in [12] is its empirical filter bank structure  ... 
doi:10.1016/j.sigpro.2011.01.018 fatcat:hy63titl4zcttjbaimrr6omn3q

Filter Bank Property of Multivariate Empirical Mode Decomposition

Naveed ur Rehman, Danilo P. Mandic
2011 IEEE Transactions on Signal Processing  
ACKNOWLEDGMENT The authors would like to thank Iran Telecommunication Research Center (ITRC) for their financial support of this research.  ...  As our simulation results show, there is a good match between theory (our derived expressions) and computer simulations.  ...  Filter Bank Property of Multivariate Empirical Mode Decomposition Naveed ur Rehman and Danilo P.  ... 
doi:10.1109/tsp.2011.2106779 fatcat:frabjasakvadfbeeby6brpibjy

Classification of Motor Imagery BCI Using Multivariate Empirical Mode Decomposition

Cheolsoo Park, David Looney, Naveed ur Rehman, Alireza Ahrabian, Danilo P. Mandic
2013 IEEE transactions on neural systems and rehabilitation engineering  
Index Terms-Brain-computer interface (BCI), electroencephalogram (EEG), empirical mode decomposition, motor imagery paradigm, noise assisted multivariate extensions of empirical mode decomposition (NA-MEMD  ...  To deal with data nonstationarity, low signal-to-noise ratio, and closely spaced frequency bands of interest, we investigate the effectiveness of recently introduced multivariate extensions of empirical  ...  extend the real-valued EMD to the bivariate or complex domain, "rotation invariant empirical mode decomposition (RIEMD)" [22] , "complex empirical mode decomposition (CEMD)" [23] and "bivariate empirical  ... 
doi:10.1109/tnsre.2012.2229296 pmid:23204288 fatcat:2ejtmm3zbjb2nloyrvmkbmlw7u

Multichannel Signal Denoising using Multivariate Variational Mode Decomposition with Subspace Projection

Peipei Cao, Huali Wang, Kaijie Zhou
2020 IEEE Access  
This paper describes a novel multichannel signal denoising approach based on multivariate variational mode decomposition (MVMD).  ...  Unlike previous MEMD (multivariate empirical mode decomposition)-based denoising methods, the proposed scheme not only has a precise mathematical framework but also can better align the common frequency  ...  In 2019, ur Rehman and Aftab [15] first proposed the multivariable variational mode decomposition (MVMD) algorithm, which is the extension of the VMD algorithm for the multivariable or multichannel data  ... 
doi:10.1109/access.2020.2988552 fatcat:kogepeyo5babtbdo4okvxdvwdi

Noise-assisted multivariate empirical mode decomposition for multichannel EMG signals

Yi Zhang, Peng Xu, Peiyang Li, Keyi Duan, Yuexin Wen, Qin Yang, Tao Zhang, Dezhong Yao
2017 BioMedical Engineering OnLine  
Methods: Based on the experimental data, a comparative study is provided by assessing the Empirical Mode Decomposition (EMD)-based approaches, EEMD, Multivariate EMD (MEMD), and Noise-Assisted MEMD (NA-MEMD  ...  However, few papers examine the temporal and spatial characteristics across multiple muscle groups in relation to multichannel EMG signals.  ...  All the authors have read and approved the manuscript. The authors will transfer copyright to the publisher upon acceptance of the manuscript. Ethics approval and consent to participate  ... 
doi:10.1186/s12938-017-0397-9 pmid:28835251 pmcid:PMC5569569 fatcat:iemuze4245fxzmsvzc7vntjqge

EEG epileptic seizures separation with multivariate empirical mode decomposition for diagnostic purposes

Tomasz M. Rutkowski, Zbigniew R. Struzik, Danilo P. Mandic
2013 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)  
We present a successful application of a soft computing approach based on the multivariate empirical mode decomposition (MEMD) method to EEG epileptic seizures separation.  ...  The results of the automatic multivatiate intrinsic mode functions (IMF) clustering allowed us to separate the seizure related spikes and sharp waves.  ...  In recent years successful developments has been reported, which are based on empirical mode decomposition (EMD) [3] and on its multivariate extension [4] .  ... 
doi:10.1109/embc.2013.6611201 pmid:24111388 dblp:conf/embc/RutkowskiSM13 fatcat:nx34443z6nbitjex7cqd4cbawq

Multivariate entropy analysis with data-driven scales

M. U. Ahmed, N. Rehman, D. Looney, T. M. Rutkowski, P. Kidmose, D. P. Mandic
2012 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)  
This is achieved by combining multivariate sample entropy with a multivariate extension of empirical mode decomposition, both datadriven multiscale techniques.  ...  Index Terms-Multivariate sample entropy, multivariate empirical mode decomposition, multivariate multiscale entropy, dynamical complexity, complexity of physiological data  ...  MULTIVARIATE EMPIRICAL MODE DECOMPOSITION The empirical mode decomposition (EMD) algorithm was developed as an adaptive approach to time-frequency analysis [11] .  ... 
doi:10.1109/icassp.2012.6288770 dblp:conf/icassp/AhmedRLRKM12 fatcat:b4e7higup5h2rnmt76zvlkespu

Epileptic Seizures Detection based on Empirical Mode Decomposition and Hilbert-Huang transform of EEG Signal

Mokhtar Mohammadi, Aso M. Darwesh
2015 Journal of University of Human Development  
The proposed method uses the application of multivariate empirical mode decomposition (MEMD) algorithm combines with the Hilbert transform as the Hilbert-Huang transform (HHT) and analyzing spectral energy  ...  EMD uses the characteristics of signals to adaptively decompose them to several intrinsic mode functions (IMFs).  ...  MULTIVARIATE EMPIRICAL MODE DECOMPOSITION For multivariate signals, the local maxima and minima may not be defined directly.  ... 
doi:10.21928/juhd.v1n2y2015.pp295-299 fatcat:ok4kwkow6fbv7i2aq6kswuaadq

THEORY OF DIGITAL FILTER BANKS REALIZED VIA MULTIVARIATE EMPIRICAL MODE DECOMPOSITION

MIN-SUNG KOH, DANILO P. MANDIC, ANTHONY G. CONSTANTINIDES
2014 Advances in Adaptive Data Analysis  
Undecimated and decimated multivariate empirical mode decomposition filter banks (MEMDFBs) are introduced in order to incorporate MEMD equipped with downsampling into any arbitrary tree structure and provide  ...  Arbitrary tree structures in decimated MEMDFBs also lead to more diverse choices in frequency bands for various multivariate applications requiring decimations.  ...  A new signal processing technique without stationary and linear assumptions was introduced in Huang et al. [1998] and termed empirical mode decomposition (EMD).  ... 
doi:10.1142/s1793536914500010 fatcat:4x73eibty5bzdpjcmsxe2lnzha

Noise-Assisted Multivariate Empirical Mode Decomposition Based Emotion Recognition

Pinar Ozel, Aydin Akan, Bulent Yilmaz
2018 Electrica  
Currently, in addition to classical time-frequency methods, emotional state data have been processed via data-driven methods such as empirical mode decomposition (EMD).  ...  To overcome these problems, this study employs a multivariate EMD and its noise-assisted version in the emotional state classification of electroencephalogram signals.  ...  Noise-Assisted Multivariate Empirical Mode Decomposition. Noise is normally a substance added in that it adds to the data bearing signal.  ... 
doi:10.26650/electrica.2018.00998 fatcat:cxojqk6tczepxncitwjcmdqfqy

Multivariate Fast Iterative Filtering for the decomposition of nonstationary signals [article]

Antonio Cicone, Enza Pellegrino
2021 arXiv   pre-print
In this work, we present a new technique for the decomposition of multivariate data, which we call Multivariate Fast Iterative Filtering (MvFIF) algorithm.  ...  in a fast and reliable manner, a uniquely defined decomposition of any multivariate signal.  ...  Subsequently, first a trivariate, and then a multivariate generalization of the standard EMD method, called Multivariate Empirical Mode Decomposition (MEMD), were introduced in [36] and [26] , respectively  ... 
arXiv:1902.04860v3 fatcat:kvqwhihwlngp7euwimj4brmedy

EMD VIA MEMD: MULTIVARIATE NOISE-AIDED COMPUTATION OF STANDARD EMD

NAVEED UR REHMAN, CHEOLSOO PARK, NORDEN E. HUANG, DANILO P. MANDIC
2013 Advances in Adaptive Data Analysis  
the proposed method, in terms of improved frequency localization and reduced modemixing, is demonstrated via simulations on electroencephalogram (EEG) data sets, over two paradigms in brain-computer interface  ...  Multivariate EMD and Its Noise-Aided Extensions Multivariate empirical mode decomposition Multivariate empirical mode decomposition (MEMD) algorithm was designed to operate for an arbitrary number of  ...  A noise-assisted approach in conjunction with multivariate empirical mode decomposition (MEMD) algorithm is proposed for the computation of empirical mode decomposition (EMD), in order to produce localized  ... 
doi:10.1142/s1793536913500076 fatcat:4slsr2luk5d23jidnkpvap7xau

Comparative study of methods for solving the correspondence problem in EMD applications

Diana Piper, Karin Schiecke, Herbert Witte, Lutz Leistritz
2016 Current Directions in Biomedical Engineering  
AbstractWe address the correspondence problem which arises when applying empirical mode decomposition (EMD) to multi-trial and multi-subject data.  ...  In order to assign IMFs with similar characteristics to each other, we compare two assignment methods, unbalanced assignment and k-cardinality assignment and two clustering algorithms, namely hierarchical  ...  (EEMD) [5] and complete ensemble empirical mode decomposition with adaptive noise (CEEMD) [6] , or are multivariate extensions of EMD such as bivariate EMD [7] , trivariate EMD and multivariate empirical  ... 
doi:10.1515/cdbme-2016-0050 fatcat:ubk6dufwqffjlhrmgmo7auz4ue

A new multivariate empirical mode decomposition method for improving the performance of SSVEP-based brain–computer interface

Yi-Feng Chen, Kiran Atal, Sheng-Quan Xie, Quan Liu
2017 Journal of Neural Engineering  
The multivariate empirical mode decomposition (MEMD) has been proposed to 16 better align the corresponding IMFs of multichannel signals [30].  ...  Empirical mode decomposition (EMD) [26] is one of such techniques. 47 49 50 51 1 2 3 , etc.  ... 
doi:10.1088/1741-2552/aa6a23 pmid:28357991 fatcat:ocpbieaxu5bgrkq66edr3vqaly

Multiband Prediction Model for Financial Time Series with Multivariate Empirical Mode Decomposition

Md. Rabiul Islam, Md. Rashed-Al-Mahfuz, Shamim Ahmad, Md. Khademul Islam Molla
2012 Discrete Dynamics in Nature and Society  
Multivariate empirical mode decomposition (MEMD) is employed here for multiband representation of multichannel financial time series together.  ...  The performance of the proposed MEMD-ARMA model is compared with classical EMD, discrete wavelet transform (DWT), and with full band ARMA model in terms of signal-to-noise ratio (SNR) and mean square error  ...  Discussion and Conclusions A novel method of multiband prediction model of financial data is implemented with multivariate empirical mode decomposition MEMD which is a time domain, data adaptive filter  ... 
doi:10.1155/2012/593018 fatcat:ybau3v6cfbgn3gbwstvzo3fpbq
« Previous Showing results 1 — 15 out of 676 results