115 research outputs found

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

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    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

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    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

    A Recursive Nonlinear System Identification Method Based on Binary Measurements

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    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

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    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)

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    LYON1-BU Santé (693882101) / SudocSudocFranceF

    Expanded haemodialysis: news from the field

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    International audienceExpanded haemodialysis (HDx) has emerged as a promising solution to improve haemodialysis effectiveness. A medium cutoff membrane allows the removal of a wider range of uraemic toxins. However, little is known about the potential interesting applications of HDx therapy. Feedback from the first routine use of HDx therapy under real-life conditions in European facilities was excellent for priming and rinse back. There was no adverse event after 5191 HDx treatments. Patients suffering from itching, restless legs syndrome, persistent asthenia or malnourishment could benefit from HDx therapy. Moreover, we discuss here the promising applications in which HDx could be valuable (myeloma, rhabdomyolysis or cardiovascular diseases). This enthusiastic message is mitigated by reminding why and how prudence should be taken in the design of future HDx studies
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