International audienceWe discuss the use of a continuous-time jump Markov process as the driving process in stochastic differential systems. Results are given on the estimation of the infinitesimal generator of the jump Markov process, when considering sample paths on random time intervals. These results are then applied within the framework of stochastic dynamical systems modeling and estimation. Numerical examples are given to illustrate both consistency and asymptotic normality of the estimator of the infinitesimal generator of the driving process. We apply these results to fatigue crack growth modeling as an example of a complex dynamical system, with applications to reliability analysis
Abstract: Uncertainty propagation and quantification has gained consider-able research attention dur...
In considering Composite Material Systems, the Markov Model is important for studying the behavior o...
THE STATISTICAL CHARACTERISTICS OF THE TIME REQUIRED BY THE CRACK SIZE TO REACH A SPEC...
International audienceWe discuss the use of a continuous-time jump Markov process as the driving pro...
International audienceIn this paper, a general framework for the modelling of physical phenomena wit...
International audienceIn this paper, we use a particular piecewise deterministic Markov process (PDM...
Chapter 10The aim of this chapter is to present dynamical systems evolving in continuous-time and pe...
Switching dynamical systems are an expressive model class for the analysis of time-series data. As i...
This paper deals with a stochastic stability concept for discrete-time Markovian jump linear systems...
Fatigue crack propagation is a stochastic phenomenon due to the inherent uncertainties originating f...
AbstractThis paper deals with a stochastic stability concept for discrete-time Markovian jump linear...
We present a novel approach to inference in conditionally Gaussian continuous time stochastic proces...
International audienceA major concern for engineers and managers nowadays is to make high quality pr...
The characteristic level of degradation of a given structure is modeled through a stochastic process...
International audienceThis chapter focuses on piecewise‐deterministic models for fatigue crack propa...
Abstract: Uncertainty propagation and quantification has gained consider-able research attention dur...
In considering Composite Material Systems, the Markov Model is important for studying the behavior o...
THE STATISTICAL CHARACTERISTICS OF THE TIME REQUIRED BY THE CRACK SIZE TO REACH A SPEC...
International audienceWe discuss the use of a continuous-time jump Markov process as the driving pro...
International audienceIn this paper, a general framework for the modelling of physical phenomena wit...
International audienceIn this paper, we use a particular piecewise deterministic Markov process (PDM...
Chapter 10The aim of this chapter is to present dynamical systems evolving in continuous-time and pe...
Switching dynamical systems are an expressive model class for the analysis of time-series data. As i...
This paper deals with a stochastic stability concept for discrete-time Markovian jump linear systems...
Fatigue crack propagation is a stochastic phenomenon due to the inherent uncertainties originating f...
AbstractThis paper deals with a stochastic stability concept for discrete-time Markovian jump linear...
We present a novel approach to inference in conditionally Gaussian continuous time stochastic proces...
International audienceA major concern for engineers and managers nowadays is to make high quality pr...
The characteristic level of degradation of a given structure is modeled through a stochastic process...
International audienceThis chapter focuses on piecewise‐deterministic models for fatigue crack propa...
Abstract: Uncertainty propagation and quantification has gained consider-able research attention dur...
In considering Composite Material Systems, the Markov Model is important for studying the behavior o...
THE STATISTICAL CHARACTERISTICS OF THE TIME REQUIRED BY THE CRACK SIZE TO REACH A SPEC...