The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Jérôme Idier - One of the best experts on this subject based on the ideXlab platform.
-
a partially collapsed gibbs sampler for unsupervised nonnegative sparse Signal Restoration
International Conference on Acoustics Speech and Signal Processing, 2021Co-Authors: Mehdi Chahine Amrouche, H Carfantan, Jérôme IdierAbstract:In this paper the problem of Restoration of unsupervised nonnegative sparse Signals is addressed in the Bayesian framework. We introduce a new probabilistic hierarchical prior, based on the Generalized Hyperbolic (GH) distribution, which explicitly accounts for sparsity. On the one hand, this new prior allows us to take into account the non-negativity. On the other hand, thanks to the decomposition of GH distributions as continuous Gaussian mean-variance mixture, a partially collapsed Gibbs sampler (PCGS) implementation is made possible, which is shown to be more efficient in terms of convergence time than the classical Gibbs sampler.
-
from bernoulli gaussian deconvolution to sparse Signal Restoration
IEEE Transactions on Signal Processing, 2011Co-Authors: Charles Soussen, Jérôme Idier, David Brie, Junbo DuanAbstract:Formulated as a least square problem under an l0 constraint, sparse Signal Restoration is a discrete optimization problem, known to be NP complete. Classical algorithms include, by increasing cost and efficiency, matching pursuit (MP), orthogonal matching pursuit (OMP), orthogonal least squares (OLS), stepwise regression algorithms and the exhaustive search. We revisit the single most likely replacement (SMLR) algorithm, developed in the mid-1980s for Bernoulli-Gaussian Signal Restoration. We show that the formulation of sparse Signal Restoration as a limit case of Bernoulli-Gaussian Signal Restoration leads to an l0-penalized least square minimization problem, to which SMLR can be straightforwardly adapted. The resulting algorithm, called single best replacement (SBR), can be interpreted as a forward-backward extension of OLS sharing similarities with stepwise regression algorithms. Some structural properties of SBR are put forward. A fast and stable implementation is proposed. The approach is illustrated on two inverse problems involving highly correlated dictionaries. We show that SBR is very competitive with popular sparse algorithms in terms of tradeoff between accuracy and computation time.
-
Efficiency of line search strategies in interior point methods for linearly constrained Signal Restoration
2011 IEEE Statistical Signal Processing Workshop (SSP), 2011Co-Authors: Emilie Chouzenoux, Saïd Moussaoui, Jérôme IdierAbstract:We discuss in this paper the influence of line search on the performances of interior point algorithms applied for constrained Signal Restoration. Interior point algorithms ensure the fulfillment of the constraints through the minimization of a criterion augmented with a barrier function. However, the presence of the barrier function can slow down the convergence of iterative descent algorithms when general-purpose line search procedures are employed. We recently proposed a line search algorithm, based on a majorization-minimization approach, which allows to handle the singularity introduced by the barrier function. We present here a comparative study of various line search strategies for the resolution of a sparse Signal Restoration problem with both primal and primal-dual interior point algorithms.
Jorge M. Seminario - One of the best experts on this subject based on the ideXlab platform.
-
molecular scale electronics a synthetic computational approach to digital computing
Journal of the American Chemical Society, 1998Co-Authors: James M Tour, And Masatoshi Kozaki, Jorge M. SeminarioAbstract:This paper outlines a design paradigm for molecular scale electronic systems. The contrast between the present bulk devices and potential molecular systems is presented along with the limitations of using bulk design philosophies for molecular-sized components. For example, the overwhelming considerations of heat dissipation on molecular scale electronic architectures are shown which demonstrate the need for dramatically different information transfer methods if these ultradense molecular devices are to be used for computation. The use of changes in electrostatic potential for information coding is suggested. The issue of Signal Restoration is addressed using a periodic external potential through the underlying substrate. Several convergent synthetic routes are shown to conjugated molecules with various potential digital device applications including a two-terminal molecular wire with a tunnel barrier, a molecular wire with a quantum well to serve as a resonant-tunneling diode, three-terminal systems with...
C. Stude - One of the best experts on this subject based on the ideXlab platform.
-
Live demonstration: Real-time audio Restoration using sparse Signal recovery
2013 IEEE International Symposium on Circuits and Systems (ISCAS), 2013Co-Authors: D. Ellasi, A. Urg, N. Felbe, H. Kaesli, Pierre Maechle, C. StudeAbstract:We demonstrate the Restoration of audio Signals corrupted by clicks and pops using techniques from sparse Signal recovery and compressive sensing. The demonstration features real-time Signal Restoration using the approximate message passing algorithm on an FPGA prototyping board. To highlight the Restoration performance of our implementation, we remove clicks and pops from old phonograph recordings in real time.
Junbo Duan - One of the best experts on this subject based on the ideXlab platform.
-
from bernoulli gaussian deconvolution to sparse Signal Restoration
IEEE Transactions on Signal Processing, 2011Co-Authors: Charles Soussen, Jérôme Idier, David Brie, Junbo DuanAbstract:Formulated as a least square problem under an l0 constraint, sparse Signal Restoration is a discrete optimization problem, known to be NP complete. Classical algorithms include, by increasing cost and efficiency, matching pursuit (MP), orthogonal matching pursuit (OMP), orthogonal least squares (OLS), stepwise regression algorithms and the exhaustive search. We revisit the single most likely replacement (SMLR) algorithm, developed in the mid-1980s for Bernoulli-Gaussian Signal Restoration. We show that the formulation of sparse Signal Restoration as a limit case of Bernoulli-Gaussian Signal Restoration leads to an l0-penalized least square minimization problem, to which SMLR can be straightforwardly adapted. The resulting algorithm, called single best replacement (SBR), can be interpreted as a forward-backward extension of OLS sharing similarities with stepwise regression algorithms. Some structural properties of SBR are put forward. A fast and stable implementation is proposed. The approach is illustrated on two inverse problems involving highly correlated dictionaries. We show that SBR is very competitive with popular sparse algorithms in terms of tradeoff between accuracy and computation time.
James M Tour - One of the best experts on this subject based on the ideXlab platform.
-
molecular scale electronics a synthetic computational approach to digital computing
Journal of the American Chemical Society, 1998Co-Authors: James M Tour, And Masatoshi Kozaki, Jorge M. SeminarioAbstract:This paper outlines a design paradigm for molecular scale electronic systems. The contrast between the present bulk devices and potential molecular systems is presented along with the limitations of using bulk design philosophies for molecular-sized components. For example, the overwhelming considerations of heat dissipation on molecular scale electronic architectures are shown which demonstrate the need for dramatically different information transfer methods if these ultradense molecular devices are to be used for computation. The use of changes in electrostatic potential for information coding is suggested. The issue of Signal Restoration is addressed using a periodic external potential through the underlying substrate. Several convergent synthetic routes are shown to conjugated molecules with various potential digital device applications including a two-terminal molecular wire with a tunnel barrier, a molecular wire with a quantum well to serve as a resonant-tunneling diode, three-terminal systems with...