3,626 research outputs found
Enhanced Recursive Reed-Muller Erasure Decoding
Recent work have shown that Reed-Muller (RM) codes achieve the erasure
channel capacity. However, this performance is obtained with maximum-likelihood
decoding which can be costly for practical applications. In this paper, we
propose an encoding/decoding scheme for Reed-Muller codes on the packet erasure
channel based on Plotkin construction. We present several improvements over the
generic decoding. They allow, for a light cost, to compete with
maximum-likelihood decoding performance, especially on high-rate codes, while
significantly outperforming it in terms of speed
Non-monotonic flow variations in a TASEP-based traffic model featuring cars searching for parking
The Totally Asymmetric Simple Exclusion Process (TASEP) is a paradigm of
out-of-equilibrium Statistical Physics that serves as a simplistic model for
one-way vehicular traffic. Since traffic is perturbed by cars cruising for
parking in many metropolises, we introduce a variant of TASEP, dubbed SFP, in
which particles are initially cruising at a slower speed and aiming to park on
one of the sites adjacent to the main road, described by a unidimensional
lattice. After parking, they pull out at a finite rate and move at a normal
speed. We show that this model, which breaks many of the conservation rules
applicable in other TASEP variants, exhibits singular features, in particular
non-monotonic variations of the steady-state current with the injection rate
and re-entrant transitions in the phase diagram, for some range of parameters.
These features are robust to variations in the update rule and the boundary
conditions.Neither the slow speed of cruising cars nor the perturbation of the
flow due to pull-out maneuvers, taken in isolation, can rationalize these
observations. Instead, they originate in a cramming (or `paper jam') effect
which results from the coupling of these mechanisms: injecting too many cars
into the system saturates the first sites of the road, which prevents parked
cars from pulling out, thus forcing cruising cars to travel farther along the
road.These strong discrepancies with even the qualitative trends of the
baseline TASEP model highlight the importance of considering the effect of
perturbations on traffic
Low-rate coding using incremental redundancy for GLDPC codes
In this paper we propose a low-rate coding method, suited for application-layer forward error correction. Depending on channel conditions, the coding scheme we propose can switch from a fixed-rate LDPC code to various low-rate GLDPC codes. The source symbols are first encoded by using a staircase or triangular LDPC code. If additional symbols are needed, the encoder is then switched to the GLDPC mode and extra-repair symbols are produced, on demand. In order to ensure small overheads, we consider irregular distributions of extra-repair symbols optimized by density evolution techniques. We also show that increasing the number of extra-repair symbols improves the successful decoding probability, which becomes very close to 1 for sufficiently many extra-repair symbols
Hopping magneto-transport via nonzero orbital momentum states and organic magnetoresistance
In hopping magnetoresistance of doped insulators, an applied magnetic field
shrinks the electron (hole) s-wave function of a donor or an acceptor and this
reduces the overlap between hopping sites resulting in the positive
magnetoresistance quadratic in a weak magnetic field, B. We extend the theory
of hopping magnetoresistance to states with nonzero orbital momenta. Different
from s-states, a weak magnetic field expands the electron (hole) wave functions
with positive magnetic quantum numbers, m > 0, and shrinks the states with
negative m in a wide region outside the point defect. This together with a
magnetic-field dependence of injection/ionization rates results in a negative
weak-field magnetoresistance, which is linear in B when the orbital degeneracy
is lifted. The theory provides a possible explanation of a large low-field
magnetoresistance in disordered pi-conjugated organic materials (OMAR).Comment: 4 pages, 3 figure
Problèmes de benchmark pour l'identiifcation de modèles à temps continu: conception, résultats et perspectives
International audienceThe problem of estimating continuous-time model parameters of linear dynamical systems using sampled time-domain input and output data has received considerable attention over the past decades and has been approached by various methods. The research topic also bears practical importance due to both its close relation to first principles modeling and equally to linear model-based control design techniques, most of them carried in continuous time. Nonetheless, as the performance of the existing algorithms for continuous-time model identification has seldom been assessed and, as thus far, it has not been considered in a comprehensive study, this practical potential of existing methods remains highly questionable. The goal of this brief paper is to bring forward a first study on this issue and to factually highlight the main aspects of interest. As such, an analysis is performed on a benchmark designed to be consistent both from a system identification viewpoint and from a control-theoretic one. It is concluded that robust initialization aspects require further research focus towards reliable algorithm development.Ce papier traite de benchmarking de l'identification de modèles à temps continu qui sont très utilisés dans l'ingiénerie
Robot recognizing vowels in a multimodal way
International audienceThis paper presents a sensory-motor architecture based on a neural network allowing a robot to recognize vowels in a multi-modal way thanks to human mimicking. The robot autonomously learns to associate its internal state to a human's vowel as an infant would to recognize vowel, and learn to associate congruent information
Problèmes de benchmark pour l'identiifcation de modèles à temps continu: conception, résultats et perspectives
International audienceThe problem of estimating continuous-time model parameters of linear dynamical systems using sampled time-domain input and output data has received considerable attention over the past decades and has been approached by various methods. The research topic also bears practical importance due to both its close relation to first principles modeling and equally to linear model-based control design techniques, most of them carried in continuous time. Nonetheless, as the performance of the existing algorithms for continuous-time model identification has seldom been assessed and, as thus far, it has not been considered in a comprehensive study, this practical potential of existing methods remains highly questionable. The goal of this brief paper is to bring forward a first study on this issue and to factually highlight the main aspects of interest. As such, an analysis is performed on a benchmark designed to be consistent both from a system identification viewpoint and from a control-theoretic one. It is concluded that robust initialization aspects require further research focus towards reliable algorithm development.Ce papier traite de benchmarking de l'identification de modèles à temps continu qui sont très utilisés dans l'ingiénerie
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