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Toutes les publications de l'ENAC en direct.
All ENAC publications.

[hal-01492702] Formulation relaxée de la séparation équilibrée d’un graphe

Publications ENAC - Mercredi, 22 mars 2017 - 16:18:43
Dans ce travail, nous nous intéressons à la formulation de variantes du problème du séparateur dans un graphe (VSP , pour Vertex Separator Problem), permettant de fournir des méthodes alternatives aux méthodes classiques de clustering

[hal-01491205] A maximum likelihood-based unscented Kalman filter for multipath mitigation in a multi-correlator based GNSS receiver

Publications ENAC - Mardi, 21 mars 2017 - 02:01:09
In complex environments, the presence or absence of multipath signals not only depends on the relative motion between the GNSS receiver and navigation satellites, but also on the environment where the receiver is located. Thus it is difficult to use a specific propagation model to accurately capture the dynamics of multipath signal parameters when the GNSS receiver is moving in urban canyons or other severe obstructions. This paper introduces a statistical model for the line-of-sight and multipath signals received by a GNSS receiver. A multi-correlator based GNSS receiver is also exploited with the advantage to fully characterizing the impact of multipath signals on the...

[hal-01490737] Introduction to the Issue on Stochastic Simulation and Optimization in Signal Processing

Publications ENAC - Samedi, 18 mars 2017 - 02:09:22
The papers in this special issue seek to report cutting edge research on stochastic simulation and optimisation methodologies, and their application to challenging SP problems that are not well addressed by existing methodologies.

[hal-01486832] Convolutional Trees for Fast Transform Learning

Publications ENAC - Mardi, 14 mars 2017 - 02:09:42
—Dictionary learning is a powerful approach for sparse representation. However, the numerical complexity of classical dictionary learning methods restricts their use to atoms with small supports such as patches. In a previous work, we introduced a model based on a composition of convolutions with sparse kernels to build large dictionary atoms with a low computational cost. The subject of this work is to consider this model at the next level, i.e., to build a full dictionary of atoms from convolutions of sparse kernels. Moreover, we further reduce the size of the representation space by organizing the convolution kernels used to build atoms into a tree structure. The...

[hal-01486838] Learning a fast transform with a dictionary

Publications ENAC - Mardi, 14 mars 2017 - 02:09:42
— A powerful approach to sparse representation, dictionary learning consists in finding a redundant frame in which the representation of a particular class of images is sparse. In practice, all algorithms performing dictionary learning iteratively estimate the dictionary and a sparse representation of the images using this dictionary. However, the numerical complexity of dictionary learning restricts its use to atoms with a small support. A way to alleviate these issues is introduced in this paper, consisting in dictionary atoms obtained by translating the composition of K convolutions with S-sparse kernels of known support. The dictionary update step associated with...

[hal-01485015] Deep fusion of vector tracking GNSS receivers and a 3D city model for robust positioning in urban canyons with NLOS signals

Publications ENAC - Vendredi, 10 mars 2017 - 02:06:04
In urban canyons, the GNSS satellite signals may travel an additional distance due to reflection and diffraction before reaching the receiver antenna. Where no direct path is available, this is called a non-line of- sight (NLOS) propagation and adds a positive bias to the geometric measured pseudorange. In this paper, we address the issue of GNSS positioning in harsh environments using constructively the NLOS signals. To exploit these biased signals, we compensate for the NLOS bias using a 3D GNSS simulation model of the environment. We use the 3D model as a priori information to characterize the additional NLOS bias. In this work, we propose a deep integration of the 3D...

[hal-01485021] Nonlinear regression using smooth Bayesian estimation

Publications ENAC - Vendredi, 10 mars 2017 - 02:06:04
This paper proposes a new Bayesian strategy for the estimation of smooth parameters from nonlinear models. The observed signal is assumed to be corrupted by an independent and non identically (colored) Gaussian distribution. A prior enforcing a smooth temporal evolution of the model parameters is considered. The joint posterior distribution of the unknown parameter vector is then derived. A Gibbs sampler coupled with a Hamiltonian Monte Carlo algorithm is proposed which allows samples distributed according to the posterior of interest to be generated and to estimate the unknown model parameters/hyperparameters. Simulations conducted with synthetic and real satellite...

[hal-01485037] Bayesian sparse estimation of migrating targets for wideband radar

Publications ENAC - Vendredi, 10 mars 2017 - 02:06:04
Wideband radar systems are highly resolved in range, which is a desirable feature for mitigating clutter. However, due to a smaller range resolution cell, moving targets are prone to migrate along the range during the coherent processing interval (CPI). This range walk, if ignored, can lead to huge performance degradation in detection. Even if compensated, conventional processing may lead to high sidelobes preventing from a proper detection in case of a multitarget scenario. Turning to a compressed sensing framework, we present a Bayesian algorithm that gives a sparse representation of migrating targets in case of a wideband waveform. Particularly, it is shown that the...

[hal-01484077] TIMED SEQUENCES: A FRAMEWORK FOR COMPUTER-AIDED COMPOSITION WITH TEMPORAL STRUCTURES

Publications ENAC - Vendredi, 10 mars 2017 - 02:03:40
The software framework we present implements a simple and generic representation of the temporal dimension of musical structures used in computer-aided composition software. These structures are modeled as ordered sets of abstract " timed items " whose actual dates can be set and determined following different strategies. The timed items can be linked to an underlying action scheduling and rendering system, and can also be used as temporal handles to perform time stretching and hierarchical synchronization operations. A graphical user interface associated with this model can be embedded as a component within musical editors. We give several examples of musical...

[hal-01205254] A New Genetic Algorithm Working on State Domain Order Statistics

Publications ENAC - Mercredi, 8 mars 2017 - 15:02:43
This paper presents a new concept of Genetic Algorithm in which an individual is coded as a domain of the state space and is evaluated with the help of order statistics. For this first version only continuous criteria has been investigated. An hypercube domain of the state space is associated with each individual and is randomly sampled according to a distribution for which asymptotic extremes are known. Regular fitnesses are computed for all the samples in each domain and are combined to produce a prospectiveness criterion. A regular GA and this new GA are compared on classical N dimensional functions such as Sphere, Step, Ackley, Griewank for dfferent values of N. A...
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