124 research outputs found
Sparse-Based Estimation Performance for Partially Known Overcomplete Large-Systems
We assume the direct sum o for the signal subspace. As a result of
post- measurement, a number of operational contexts presuppose the a priori
knowledge of the LB -dimensional "interfering" subspace and the goal is to
estimate the LA am- plitudes corresponding to subspace . Taking into account
the knowledge of the orthogonal "interfering" subspace \perp, the Bayesian
estimation lower bound is de-
rivedfortheLA-sparsevectorinthedoublyasymptoticscenario,i.e. N,LA,LB -> \infty
with a finite asymptotic ratio. By jointly exploiting the Compressed Sensing
(CS) and the Random Matrix Theory (RMT) frameworks, closed-form expressions for
the lower bound on the estimation of the non-zero entries of a sparse vector of
interest are derived and studied. The derived closed-form expressions enjoy
several interesting features: (i) a simple interpretable expression, (ii) a
very low computational cost especially in the doubly asymptotic scenario, (iii)
an accurate prediction of the mean-square-error (MSE) of popular sparse-based
estimators and (iv) the lower bound remains true for any amplitudes vector
priors. Finally, several idealized scenarios are compared to the derived bound
for a common output signal-to-noise-ratio (SNR) which shows the in- terest of
the joint estimation/rejection methodology derived herein.Comment: 10 pages, 5 figures, Journal of Signal Processin
Informed stego-systems in active warden context: statistical undetectability and capacity
Several authors have studied stego-systems based on Costa scheme, but just a
few ones gave both theoretical and experimental justifications of these schemes
performance in an active warden context. We provide in this paper a
steganographic and comparative study of three informed stego-systems in active
warden context: scalar Costa scheme, trellis-coded quantization and spread
transform scalar Costa scheme. By leading on analytical formulations and on
experimental evaluations, we show the advantages and limits of each scheme in
term of statistical undetectability and capacity in the case of active warden.
Such as the undetectability is given by the distance between the stego-signal
and the cover distance. It is measured by the Kullback-Leibler distance.Comment: 6 pages, 8 figure
Bayesian Lower Bounds for Dense or Sparse (Outlier) Noise in the RMT Framework
Robust estimation is an important and timely research subject. In this paper,
we investigate performance lower bounds on the mean-square-error (MSE) of any
estimator for the Bayesian linear model, corrupted by a noise distributed
according to an i.i.d. Student's t-distribution. This class of prior
parametrized by its degree of freedom is relevant to modelize either dense or
sparse (accounting for outliers) noise. Using the hierarchical Normal-Gamma
representation of the Student's t-distribution, the Van Trees' Bayesian
Cram\'er-Rao bound (BCRB) on the amplitude parameters is derived. Furthermore,
the random matrix theory (RMT) framework is assumed, i.e., the number of
measurements and the number of unknown parameters grow jointly to infinity with
an asymptotic finite ratio. Using some powerful results from the RMT,
closed-form expressions of the BCRB are derived and studied. Finally, we
propose a framework to fairly compare two models corrupted by noises with
different degrees of freedom for a fixed common target signal-to-noise ratio
(SNR). In particular, we focus our effort on the comparison of the BCRBs
associated with two models corrupted by a sparse noise promoting outliers and a
dense (Gaussian) noise, respectively
Joint ML calibration and DOA estimation with separated arrays
This paper investigates parametric direction-of-arrival (DOA) estimation in a
particular context: i) each sensor is characterized by an unknown complex gain
and ii) the array consists of a collection of subarrays which are substantially
separated from each other leading to a structured noise covariance matrix. We
propose two iterative algorithms based on the maximum likelihood (ML)
estimation method adapted to the context of joint array calibration and DOA
estimation. Numerical simulations reveal that the two proposed schemes, the
iterative ML (IML) and the modified iterative ML (MIML) algorithms for joint
array calibration and DOA estimation, outperform the state of the art methods
and the MIML algorithm reaches the Cram\'er-Rao bound for a low number of
iterations
Relaxed concentrated MLE for robust calibration of radio interferometers
In this paper, we investigate the calibration of radio interferometers in
which Jones matrices are considered to model the interaction between the
incident electromagnetic field and the antennas of each station. Specifically,
perturbation effects are introduced along the signal path, leading to the
conversion of the plane wave into an electric voltage by the receptor. In order
to design a robust estimator, the noise is assumed to follow a spherically
invariant random process (SIRP). The derived algorithm is based on an iterative
relaxed concentrated maximum likelihood estimator (MLE), for which closed-form
expressions are obtained for most of the unknown parameters
Estimation des Directions D'Arrivées incorporant un a priori : Algorithmes et Variances Théoriques
Dans le contexte de l'estimation des Directions D'Arrivées (DDA), on peut parfois considérer que nous connaissons à priori (de manière exacte ou estimée) un ensemble de M-S DDA parmi un total de M. Dans ce contexte, des schémas d'estimation ont été proposés afin de tenir compte de cette connaissance dans le but d'améliorer la localisation des M sources d'intérêt. Ces approches se basent sur la déflation orthogonale du sous-espace signal. Dans [10], nous avons établi et analysé la Brone de Cramer-Rao (BCR) correspondante à ce type de modèle et nous avons montré qu'une connaissance a priori d'un ensemble de DDA est bénéfique uniquement pour des sources corrélées et de DDA proches. En particulier, dans le cas de sources non corrélées de DDA proches, les approches basées sur la déflation orthogonale n'améliorent pas l'estimation des DDA d'intérêt. Une solution possible pour résoudre ce problème est d'exploiter une déflation oblique. Selon ce principe, nous proposons deux algorithmes de type MinNorm dont nous caractérisons les performances théoriques
Depolarization-induced translocation of the RNA-binding protein Sam68 to the dendrites of hippocampal neurons.
International audienceThe traffic and expression of mRNAs in neurons are modulated by changes in neuronal activity. The regulation of neuronal RNA-binding proteins is therefore currently receiving attention. Sam68 is a ubiquitous nuclear RNA-binding protein implicated in post-transcriptional processes such as signal-dependent splice site selection. We show that Sam68 undergoes activity-responsive translocation to the soma and dendrites of hippocampal neurons in primary culture. In unstimulated neurons transiently expressing a GFP-Sam68 fusion protein, 90% of the cells accumulated the protein exclusively in the nucleus, and 4% showed extension of GFP-Sam68 to the dendrites. This nuclear expression pattern required the integrity of the Sam68 N-terminus. When present, the dendritic GFP-Sam68 formed granules, 26% of which were colocalized with ethidium bromide-stained RNA clusters. Most of the GFP-Sam68 granules were completely stationary, but a few moved in either a retrograde or anterograde direction. Following depolarization by 25 mM KCl, 50% of neurons displayed dendritic GFP-Sam68. GFP-Sam68 invaded the dendrites after 2 hours with high KCl, and returned to the nucleus within 3 hours after termination of the KCl treatment. A control GFP fusion derived from the SC-35 splicing factor remained fully nuclear during depolarization. No significant change was observed in the phosphorylation of Sam68 after depolarization. Translocation of Sam68 to the distal dendrites was microtubule dependent. Blockade of calcium channels with nimodipine abolished the translocation. Furthermore, inhibition of CRM-1-mediated nuclear export by leptomycin B partially prevented the depolarization-induced nuclear efflux of GFP-Sam68. These results support the possible involvement of Sam68 in the activity-dependent regulation of dendritic mRNAs
Modèles sinusoïdaux étendus pour le codage audio
- Dans cet article, on commence par faire un bref panorama de quelques extensions du modèle sinusoïdal. Ensuite, dans une optique de codage du signal audio, on retient deux représentations, nommées modèle sinusoïdal amorti exponentiellement et modèle sinusoïdal amorti et retardé. On montre alors leur utilité vis-à -vis de phénomènes audio identifiés (transitoires, pseudostationnaires, ...). En outre, on propose un algorithme d'estimation des paramètres de modèle alliant une approche Haute-Résolution et un schéma par déflation. Finalement, nous montrons en quoi ces deux modèles sont des solutions viables en tant que "briques de base" dans une architecture de codage sinusoïdal audio
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