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