The aim of this paper is to present a new method to generate timed input/output automata from Estelle speciications. The main idea is to extend the ESTELLE language with a new constructor : TVAR, which permits the deenition of clocks to be used for time constraints. The second concept is to propose some semantic rules in order to deene how to take into account clock constraints in the ESTELLE s...

This paper addresses optimal estimation for time varying autoregressive (TVAR) models. First, we propose a statistical model on the time evolution of the frequencies, moduli and real poles instead of a standard model on the AR coefficients as it makes more sense from a physical viewpoint. Second, optimal estimation involves solving a complex optimal filtering problem which does not admit any cl...

It is often needed to label electroencephalogram (EEG) signals by segments of similar characteristics that are particularly meaningful to clinicians and for assessment by neurophysiologists. Within each segment, the signals are considered statistically stationary, usually with similar characteristics such as amplitude and/or frequency. In order to detect the segments boundaries of a signal, we ...

In order to protect stakeholders of insurance companies and financial institutions against adverse outcomes of risky businesses, regulators and senior management use capital allocation techniques. For enterprise-wide risk management, it has become important to calculate the contribution of each risk within a portfolio. For that purpose, bivariate lower and upper orthant tail value-at-risk can b...

| This work presents a new method using time-varying autoregressive modelling for the assessment of heart rate signals stationarity in patients before the onset of ventricular tachyarrhythmias, including comparison with a control group. A general sta-tionarity trend is reported for all subjects, and particularly no signiicant change is observed before an arrhythmic event. Evaluation of the mode...

In this paper, we consider the problem of optimal reinsurance design, when risk is measured by TrTVaR measure. We study models from perspectives both insurers and reinsurers. To reduce ex-post moral hazard, assume that contracts satisfy principle indemnity incentive-compatible constraint. When losses an insurer a reinsurer are measures, obtain explicit forms Pareto-optimal under expected value ...

Supermassive black hole binaries (SMBHBs) produced in galaxy mergers are thought to complete their coalescence, at separations r ∼ < rGW ≈ 10 (MBH/10M⊙) pc, as their orbit decays due to the emission of gravitational waves (GWs). Here we propose that it may be possible to identify such GW–driven inspirals statistically in a deep electromagnetic (EM) survey for variable sources, before the Laser ...

In this work, we study the problem of online adaptive forecasting for locally stationary Time Varying Autoregressive processes (TVAR). The Normalized Mean Least Squares algorithm (NMLS) is an online stochastic gradient method which has been shown to perform efficiently, provided that the gradient step size is well chosen. This choice highly depends on the smoothness exponent of the evolving par...