Results 241 to 250 of about 858,701 (293)
Some of the next articles are maybe not open access.
Advances in Adaptive Data Analysis, 2010
Empirical Mode Decomposition (EMD) has been widely used to analyze non-stationary and nonlinear signal by decomposing data into a series of intrinsic mode functions (IMFs) and a trend function through sifting processes. For lack of a firm mathematical foundation, the implementation of EMD is still empirical and ad hoc.
Zhaohua Wu, Nordén E Huang
exaly +2 more sources
Empirical Mode Decomposition (EMD) has been widely used to analyze non-stationary and nonlinear signal by decomposing data into a series of intrinsic mode functions (IMFs) and a trend function through sifting processes. For lack of a firm mathematical foundation, the implementation of EMD is still empirical and ad hoc.
Zhaohua Wu, Nordén E Huang
exaly +2 more sources
THE UNIQUENESS OF THE INSTANTANEOUS FREQUENCY BASED ON INTRINSIC MODE FUNCTION
Advances in Adaptive Data Analysis, 2013It has been claimed that any expression of a(t) cos θ(t) with a(t) as the instantaneous amplitude and cos θ(t) as the carrier varying along with the phase θ(t) could not be uniquely defined. However, based on the fact that a(t) cos θ(t) with all its variational forms have the same numerical value at any given time, we propose the existence of a unique
Nordén E Huang +2 more
exaly +2 more sources
A PDE characterization of the intrinsic mode functions
2009 IEEE International Conference on Acoustics, Speech and Signal Processing, 2009For the first time, a proof of the sifting process (SP) and so the empirical mode decomposition (EMD), is given. For doing this, lower and upper envelopes are modeled in a more convenient way that helps us prove the convergence of the SP towards a solution of a partial differential equation (PDE).
El-Hadji Samba Diop +2 more
openaire +1 more source
Intrinsic mode functions for gait recognition
2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512), 2004Gait recognition is an attractive biometric as it is unobtrusive and can be used for recognition from a distance. A number of methods have been proposed by different researchers in the recent past for this purpose. Most of these methods analyze gait as a linear and stationary signal.
Prem Kuchi, Sethuraman Panchanathan
openaire +1 more source
Analysis of the Intrinsic Mode Functions for Speaker Information
Speech Communication, 2017Abstract This work explores the utility of the time-domain signal components, or the Intrinsic Mode Functions (IMFs), of speech signals’, as generated from the data-adaptive filterbank nature of Empirical Mode Decomposition (EMD), in characterizing speakers for the task of text-independent Speaker Verification (SV). A modified version of EMD
Rajib Sharma +3 more
openaire +1 more source
A PDE model for 2D intrinsic mode functions
2009 16th IEEE International Conference on Image Processing (ICIP), 2009In this paper, we provide some theoretical contributions on the study of the 2D empirical mode decomposition (EMD). For doing this, we model the 2D sifting process (SP) in a suitable way, which helps us prove its convergence. Indeed, we prove that the 2D SP converges towards the solution of a fourth order partial differential equation (PDE).
El-Hadji Samba Diop +2 more
openaire +1 more source
Detection of periodic components from intrinsic mode function
2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2017The empirical mode decomposition (EMD) combines with Hilbert Transform is a common method of nonlinear and non-stationary signal time frequency analysis. Signal can be decomposed into different intrinsic mode functions (IMF) through the EMD. Each IMF represents a simple oscillation which provides meaningful instantaneous frequency through Hilbert ...
Cong Feng, Hui Li
openaire +1 more source
Analysis of Simulated Heart Sounds by Intrinsic Mode Functions
2006 International Conference of the IEEE Engineering in Medicine and Biology Society, 2006The mechanisms involved in the generation of heart sounds have always been of interest, mainly for diagnosis purposes. As a result, mathematical models have been proposed for first (S1) and second (S2) heart sounds and different efforts have been made to select the best signal processing tool to analyze them.
Sonia Charleston-Villalobos +2 more
openaire +2 more sources
Analysis of 2D intrinsic mode function
2009 International Conference on Test and Measurement, 2009The definition of 2D IMF is very important for bidimensional empirical mode decomposition of images. V. Vatchev analyzed 1D IMF in his doctoral dissertation, and introduced the concept of weak-IMF which point out that the solution of Sturm-Liouville equations can be regarded as 1D weak-IMF.
null Jincai Chang +3 more
openaire +1 more source