International audienceIn this paper we propose a new method called Spectral Intrinsic Decomposition (SID) for the representation of non-linear signals. This approach is based on the spectral decomposition of Partial Differential Equations (PDE)- based operators which interpolate the characteristic points of a signal. The SID's components which are the eigenvectors of these PDE interpolation operators underlie the new signal decomposition-reconstruction method. The usefulness and the efficiency of this method is illustrated, in signal reconstruction or denoising aim, on some examples using artifical and pathological signals
This paper presents a new state-space method for spectral estimation that performs decimation by any...
The empirical mode decomposition (EMD) is a popular tool that is valid for nonlinear and nonstationa...
This book provides comprehensive, graduate-level treatment of analog and digital signal analysis sui...
International audienceThis paper presents a new signal denoising method based on the classical three...
We propose an operator-based method of adaptive signal decomposition, whereby a local narrow band si...
Signal denoising based on the adaptive Fourier decomposition (AFD) is investigated and an approach, ...
peer reviewedA generalized iterative algorithm for spectral signal deconvolution is presented in thi...
Signal denoising based on the adaptive Fourier decomposition (AFD) is investigated and an approach, ...
The Adaptive Fourier Decomposition (AFD) is a novel signal decomposition algorithm that can describe...
A novel approach to the recognition of the signals degraded by a linear time-inwtriant system with a...
Speech enhancement is performed in a wide and varied range of instruments and systems. In this paper...
Prony’s method approximates a sequence of data points by a linear superposition of complex exponenti...
We propose the discrete linear chirp transform (DLCT) for decomposing a non-stationary signal into i...
This paper considers the problem to reconstruct and approximate multidimensional signals from nonuni...
Abstract. A digital signal processing based on a representation over additive algebra is discussed. ...
This paper presents a new state-space method for spectral estimation that performs decimation by any...
The empirical mode decomposition (EMD) is a popular tool that is valid for nonlinear and nonstationa...
This book provides comprehensive, graduate-level treatment of analog and digital signal analysis sui...
International audienceThis paper presents a new signal denoising method based on the classical three...
We propose an operator-based method of adaptive signal decomposition, whereby a local narrow band si...
Signal denoising based on the adaptive Fourier decomposition (AFD) is investigated and an approach, ...
peer reviewedA generalized iterative algorithm for spectral signal deconvolution is presented in thi...
Signal denoising based on the adaptive Fourier decomposition (AFD) is investigated and an approach, ...
The Adaptive Fourier Decomposition (AFD) is a novel signal decomposition algorithm that can describe...
A novel approach to the recognition of the signals degraded by a linear time-inwtriant system with a...
Speech enhancement is performed in a wide and varied range of instruments and systems. In this paper...
Prony’s method approximates a sequence of data points by a linear superposition of complex exponenti...
We propose the discrete linear chirp transform (DLCT) for decomposing a non-stationary signal into i...
This paper considers the problem to reconstruct and approximate multidimensional signals from nonuni...
Abstract. A digital signal processing based on a representation over additive algebra is discussed. ...
This paper presents a new state-space method for spectral estimation that performs decimation by any...
The empirical mode decomposition (EMD) is a popular tool that is valid for nonlinear and nonstationa...
This book provides comprehensive, graduate-level treatment of analog and digital signal analysis sui...