Convergence Analysis of an Online Approach to Parameter Estimation Problems Based on Binary Noisy Observations

International audienceThe convergence analysis of an online system identification method based on binary-quantized observations is presented in this paper. This recursive algorithm can be applied in the case of finite impulse response (FIR) systems and exhibits low computational complexity as well as low storage requirement. This method, whose practical requirement is a simple 1-bit quantizer, implies low power consumption and minimal silicon area, and is consequently well-adapted to the test of microfabricated devices. The convergence in the mean of the method is studied in the presence of measurement noise at the input of the quantizer. In particular, a lower bound of the correlation coe cient between the nominal and the estimated system parameters is found. Some simulation results are then given in order to illustrate this result and the assumptions necessary for its derivation are discusse

Etude du risque systématique de mortalité

The aim of this paper is to propose a realistic and operational model to quantify the systematic risk of mortality included in an engagement of retirement. The model presented is built on the basis of model of Lee-Carter. The stochastic prospective tables thus built make it possible to project the evolution of the random mortality rates in the future and to quantify the systematic risk of mortality.Prospective tables, extrapolation, adjustment, life annuities, stochastic mortality

Vieillissement de la population, gérontocroissance et marché du logement.

Personnes âgées; Logement;

Potential Growth in the EU : Prospects from Technical Progress and Eastern Enlargment.

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A Recursive Nonlinear System Identification Method Based on Binary Measurements

An online approach to nonlinear system identification based on binary observations is presented in this paper. This recursive method is a nonlinear extension of the LMS-like (least-mean-squares) basic identification method using binary observations (LIMBO). It can be applied in the case of weakly nonlinear Duffing oscillator coupled with a linear system characterized by a finite impulse response. It is then possible to estimate both Duffing and impulse response coefficients knowing only the system input and the sign of the system output. The impulse response is identified up to a positive multiplicative constant. The proposed method is compared in terms of convergence speed and estimation quality with the usual LMS approach, which is not based on binary observations

LIMBO self-test method using binary input and dithering signals

Abstract—An online approach to system identification based on the least-mean squares (LMS) algorithm is presented in this paper. This recursive method is actually an extended version of the LMS-like identification method based on binary observations (LIMBO), whose practical requirement is a simple comparator (1-bit quantizer). This method can be applied in the case of finite impulse response (FIR) systems in the presence of noise and offset at the comparator input. Moreover, contrary to classical LIMBO approach, the unknown parameters are rigorously identified, and not up to a positive multiplicative constant. The idea consists in introducing a known dithering signal at the input of the quantizer, which acts as reference amplitude and allows us to identify the gain of the system. Some simulation results are given in order to compare the performances of this extended version of LIMBO with the usual one, in terms of convergence speed and estimation quality. Index Terms—system identification, self-test, binary data processing, micro-systems I

Etude des néphropathies ischémiques par imagerie médicale (mise en place d'un essai clinique)

LYON1-BU Santé (693882101) / SudocSudocFranceF

Pronostic des grossesses des patientes présentant une insuffisance rénale terminale

La grossesse en hémodialyse est rare et associée à des complications materno-foetales importantes. L'objectif de cette étude est de décrire et d'identifier les facteurs influençant le déroulement des grossesses chez les patientes hémodialysées ainsi que de comparer le pronostic des grossesses en hémodialyse et après transplantation rénale. Il s'agit d'une étude descriptive rétrospective et multicentrique, incluant des patientes hémodialysées et des patientes transplantées enceintes. Sur 26 grossesses étudiées en hémodialyse, la durée hebdomadaire moyenne de dialyse est de 17. 7+-4 heures avec une concentration d'urée moyenne de 15.1+-4.4 mmol/1. La survie foetale est de 81% avec un terme moyen de 33.8+-0.8 SA et un poids de naissance moyen de 1951+-157g. Une initiation précoce de la dialyse quotidienne, une concentration d'urée prédialytique plus basse ainsi qu'une concentration d'hémoglobine plus élevée améliorent le pronostic foetal. Comparées à 17 grossesses survenues après transplantation rénale, la survie foetale, le poids de naissance et le terme sont similaires. Notre étude met en évidence une survie foetale en hémodialyse comparable à celle observée chez les patientes transplantées, mais toutefois nettement inférieure à celle observée dans la population généraleLYON1-BU Santé (693882101) / SudocSudocFranceF