International audienceWe give an example of a sequential dynamical system consisting of intermittent-type maps which exhibits loss of memory with a polynomial rate of decay. A uniform bound holds for the upper rate of memory loss. The maps may be chosen in any sequence, and the bound holds for all compositions. 0 Introduction The notion of loss of memory for non-equilibrium dynamical systems was introduced in the 2009 paper by Ott, Stenlund and Young [10]; they wrote: Let ρ0 denote an initial probability density w.r.t. a reference measure m, and suppose its time evolution is given by ρt. One may ask if these probability distributions retain memories of their past. We will say a system loses its memory in the statistical sense if for two ini...
We prove the asymptotic devcay of the solution u to an initial andboundary value problem related to ...
In this paper we study the evolution of sequential dynamical systems (SDS) asaresult of the erroneou...
Established stochastic models for discrete-time long-memory processes are linear and Gaussian and co...
International audienceWe give an example of a sequential dynamical system consisting of intermittent...
Abstract. This paper discusses the evolution of probability distributions for certain time-dependent...
International audienceWe prove a concentration inequality for sequential dynamical systems of the un...
A chaotic signal loses the memory of the initial conditions with time, and the future behavior becom...
We propose here a new method to characterize the loss of memory with time in a chaotic system from a...
Classical dynamical systems involves the study of the long-time behavior of a fixed map or vector fi...
The first chapter, devoted to random systems, we establish an abstract functional framework, includi...
There are two parts in this dissertation. In the first part we prove that genuine nonuniformly hyper...
textThis dissertation investigates the evolution of probability densities under the Frobenius-Perro...
Dans cette thèse, nous nous intéressons aux propriétés statistiques des systèmes dynamiques aléatoir...
International audienceWe establish self-norming central limit theorems for non-stationary time serie...
To make progress in understanding the issue of memory loss and history dependence in evolving comple...
We prove the asymptotic devcay of the solution u to an initial andboundary value problem related to ...
In this paper we study the evolution of sequential dynamical systems (SDS) asaresult of the erroneou...
Established stochastic models for discrete-time long-memory processes are linear and Gaussian and co...
International audienceWe give an example of a sequential dynamical system consisting of intermittent...
Abstract. This paper discusses the evolution of probability distributions for certain time-dependent...
International audienceWe prove a concentration inequality for sequential dynamical systems of the un...
A chaotic signal loses the memory of the initial conditions with time, and the future behavior becom...
We propose here a new method to characterize the loss of memory with time in a chaotic system from a...
Classical dynamical systems involves the study of the long-time behavior of a fixed map or vector fi...
The first chapter, devoted to random systems, we establish an abstract functional framework, includi...
There are two parts in this dissertation. In the first part we prove that genuine nonuniformly hyper...
textThis dissertation investigates the evolution of probability densities under the Frobenius-Perro...
Dans cette thèse, nous nous intéressons aux propriétés statistiques des systèmes dynamiques aléatoir...
International audienceWe establish self-norming central limit theorems for non-stationary time serie...
To make progress in understanding the issue of memory loss and history dependence in evolving comple...
We prove the asymptotic devcay of the solution u to an initial andboundary value problem related to ...
In this paper we study the evolution of sequential dynamical systems (SDS) asaresult of the erroneou...
Established stochastic models for discrete-time long-memory processes are linear and Gaussian and co...