Singular spectrum analysis for effective feature extraction in hyperspectral imaging [PDF]
, 2014 As a very recent technique for time series analysis, Singular Spectrum Analysis (SSA) has been applied in many diverse areas, where an original 1D signal can be decomposed into a sum of components including varying trends, oscillations and noise ...
Zabalza, Jaime +4 more
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Investigating properties of the cardiovascular system using innovative analysis algorithms based on ensemble empirical mode decomposition [PDF]
, 2012 This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited - Copyright @ 2012 Jia-Rong Yeh et al ...
Lin, TY +5 more
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An Alternative Formulation for the Empirical Mode Decomposition [PDF]
IEEE Transactions on Signal Processing, 2012 The Empirical Mode Decomposition (EMD) is a relatively new adaptive method for multicomponent signal representation which allows for analyzing nonlinear and nonstationary signals. In spite of its lack of mathematical foundations, very few papers are dedicated to defining new decompositions that would preserve the interesting properties of the EMD while
Thomas Oberlin +2 more
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Empirical mode decomposition with missing values [PDF]
SpringerPlus, 2016 This paper considers an improvement of empirical mode decomposition (EMD) in the presence of missing data. EMD has been widely used to decompose nonlinear and nonstationary signals into some components according to intrinsic frequency called intrinsic mode functions.
Kim, Donghoh, Oh, Hee-Seok
openaire +2 more sources
Multi Sensor Image Fusion using Empirical Mode Decomposition [PDF]
, 2013 Image fusion is a process of combining relevant information from two or more images from different sensors based on certain algorithm. Many algorithms have been proposed for pixel level image fusion.
Naidu, VPS, Shakthipriya, VS
core
Improved EMD Using Doubly-Iterative Sifting and High Order Spline Interpolation [PDF]
, 2008 Empirical mode decomposition (EMD) is a signal analysis method which has received much attention lately due to its application in a number of fields. The main disadvantage of EMD is that it lacks a theoretical analysis and, therefore, our understanding ...
Yannis Kopsinis +4 more
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Journal of Low Frequency Noise, Vibration and Active Control, 2021 Technology that measures bridge responses when a vehicle is crossing over it for structural health monitoring has been under development for approximately a decade.
Feng Xiao +3 more
doaj +1 more source
Artifact reduction in multichannel pervasive EEG using hybrid WPT-ICA and WPT-EMD signal decomposition techniques [PDF]
, 2014 In order to reduce the muscle artifacts in multi-channel pervasive Electroencephalogram (EEG) signals, we here propose and compare two hybrid algorithms by combining the concept of wavelet packet transform (WPT), empirical mode decomposition (EMD) and ...
Koushik Maharatna +7 more
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Sparse Reconstruction for Enhancement of the Empirical Mode Decomposition-Based Signal Denoising
IEEE Access, 2020 Effective signal denoising methods are essential for science and engineering. In general, denoising algorithms may be either linear or non-linear. Most of the linear ones are unable to remove the noise from the real-world measurements.
Krzysztof Brzostowski
doaj +1 more source
EMD-Based Filtering Using Similarity Measure Between Probability Density Functions of IMFs [PDF]
, 2014 This paper introduces a new signal-filtering which combines the empirical mode decomposition (EMD) and a similarity measure. A noisy signal is adaptively broken down into oscillatory components called intrinsic mode functions (IMFs) by EMD followed by an
DARE, Delphine +4 more
core +1 more source