The concepts of intrinsic mode functions and mono-components are investigated in rela-tion to the empirical mode decomposition. Mono-components are defined to be the functions for which non-negative analytic instantaneous frequency is well defined. We show that a great variety of functions are mono-components based on which adaptive decomposition of signals are theoretically possible. We justify the role of empirical mode decomposition in signal decomposition in relation to mono-components
Empirical Mode Decomposition (EMD) is an adaptive and data-driven approach for analyzing multi-compo...
International audienceA novel Empirical Mode Decomposition (EMD) algorithm, called 2T-EMD, for both ...
Signal decomposition (SD) approaches aim to decompose non-stationary signals into their constituent ...
We introduce the concept adaptive decomposition of signals into basic build-ing blocks, of which eac...
Abstract The paper reviews some recent progress on adaptive signal decom-position into mono-componen...
The ‘empirical mode decomposition ’ (EMD) method has been recently proposed to deal with nonlinear a...
This paper outlines the application of the empirical mode decomposition (EMD) to a frequency domain ...
[[abstract]]A new nonlinear technique for time frequency analysis, referred to as empirical mode dec...
International audienceThe empirical mode decomposition (EMD) is a relatively recent method introduce...
19 pages, 7 figures. Submitted to IEEE Trans. on Signal Proc.This paper investigates how Empirical M...
The Empirical Mode Decomposition (EMD) is a signal analysis method that separates multi-component si...
Conference PaperThis paper describes a new technique, called <i>Empirical Mode Decomposition</i> (EM...
We propose the discrete linear chirp transform (DLCT) for decomposing a non-stationary signal into i...
The empirical mode decomposition (EMD) is a popular tool that is valid for nonlinear and nonstationa...
A method of signal decomposition on sinusoidal components (intrinsic mode functions), audio coding, ...
Empirical Mode Decomposition (EMD) is an adaptive and data-driven approach for analyzing multi-compo...
International audienceA novel Empirical Mode Decomposition (EMD) algorithm, called 2T-EMD, for both ...
Signal decomposition (SD) approaches aim to decompose non-stationary signals into their constituent ...
We introduce the concept adaptive decomposition of signals into basic build-ing blocks, of which eac...
Abstract The paper reviews some recent progress on adaptive signal decom-position into mono-componen...
The ‘empirical mode decomposition ’ (EMD) method has been recently proposed to deal with nonlinear a...
This paper outlines the application of the empirical mode decomposition (EMD) to a frequency domain ...
[[abstract]]A new nonlinear technique for time frequency analysis, referred to as empirical mode dec...
International audienceThe empirical mode decomposition (EMD) is a relatively recent method introduce...
19 pages, 7 figures. Submitted to IEEE Trans. on Signal Proc.This paper investigates how Empirical M...
The Empirical Mode Decomposition (EMD) is a signal analysis method that separates multi-component si...
Conference PaperThis paper describes a new technique, called <i>Empirical Mode Decomposition</i> (EM...
We propose the discrete linear chirp transform (DLCT) for decomposing a non-stationary signal into i...
The empirical mode decomposition (EMD) is a popular tool that is valid for nonlinear and nonstationa...
A method of signal decomposition on sinusoidal components (intrinsic mode functions), audio coding, ...
Empirical Mode Decomposition (EMD) is an adaptive and data-driven approach for analyzing multi-compo...
International audienceA novel Empirical Mode Decomposition (EMD) algorithm, called 2T-EMD, for both ...
Signal decomposition (SD) approaches aim to decompose non-stationary signals into their constituent ...