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This work defines two classes of processes, that we term {\it tempered fractional multistable motion} and {\it tempered multifractional stable motion}. They are extensions of fractional multistable motion and multifractional stable motion,…

Probability · Mathematics 2019-07-04 Xiequan Fan , Jacques Lévy Véhel

This technical note studies Lyapunov-like conditions to ensure a class of dynamical systems to exhibit predefined-time stability. The origin of a dynamical system is predefined-time stable if it is fixed-time stable and an upper bound of…

Following the definition of perturbed metric space, in this paper, some fixed point theorems are established for $ F $-perturbed mappings in complete perturbed metric spaces and justify the result by counter example. Finally, an application…

Metric Geometry · Mathematics 2026-04-06 Dipti Barman , T. Bag

We study a particular class of moving average processes which possess a property called localisability. This means that, at any given point, they admit a ``tangent process'', in a suitable sense. We give general conditions on the kernel g…

Probability · Mathematics 2009-06-25 Kenneth Falconer , Ronan Le Guével , Jacques Lévy-Véhel

We introduce an index based on information theory to quantify the stationarity of a stochastic process.The index compares on the one hand the information contained in the increment at the time scale $\tau$ of the process at time $t$ with,…

Data Analysis, Statistics and Probability · Physics 2021-12-02 Carlos Granero-Belinchon , Stéphane G. Roux , Nicolas B. Garnier

For a non-stationary or non-ergodic marked point process (MPP) on $\R^d$, the definition of averages becomes ambiguous as the process might have a different stochastic behavior in different realizations (non-ergodicity) or in different…

Probability · Mathematics 2012-10-05 Alexander Malinowski , Martin Schlather , Zhengjun Zhang

We introduce Markov Neural Processes (MNPs), a new class of Stochastic Processes (SPs) which are constructed by stacking sequences of neural parameterised Markov transition operators in function space. We prove that these Markov transition…

Machine Learning · Statistics 2023-05-26 Jin Xu , Emilien Dupont , Kaspar Märtens , Tom Rainforth , Yee Whye Teh

The topic of this manuscript is the stability analysis of continuous-time switched nonlinear systems with constraints on the admissible switching signals. Our particular focus lies in considering signals characterized by upper and lower…

Optimization and Control · Mathematics 2024-01-17 Matteo Della Rossa

We study a class of self-similar processes with stationary increments belonging to higher order Wiener chaoses which are similar to Hermite processes. We obtain an almost sure wavelet-like expansion of these processes. This allows us to…

Probability · Mathematics 2019-08-20 Benjamin Arras

Finding separable certificates of stability is important for tractability of analysis methods for large-scale networked systems. In this paper we consider the question of when a nonlinear system which is contracting, i.e. all solutions are…

Systems and Control · Computer Science 2017-04-11 Ian R. Manchester , Jean-Jacques E. Slotine

Finite metric spaces arise in many different contexts. Enormous bodies of data, scientific, commercial and others can often be viewed as large metric spaces. It turns out that the metric of graphs reveals a lot of interesting information.…

Combinatorics · Mathematics 2007-05-23 Nathan Linial

Monotone L\'evy processes with additive increments are defined and studied. It is shown that these processes have a natural Markov structure and their Markov transition semigroups are characterized using the monotone L\'evy-Khintchine…

Probability · Mathematics 2021-04-21 Uwe Franz , Naofumi Muraki

We present a class of Gauss-Markov processes which can be represented as space-time scaled stationary Ornstein-Uhlenbeck processes defined on the real line. We give several explicit examples of the representation for certain Gauss bridge…

Probability · Mathematics 2019-01-28 Matyas Barczy , Peter Kern

A family of self-similar and translation-invariant random sup-measures with long-range dependence are investigated. They are shown to arise as the limit of the empirical random sup-measure of a stationary heavy-tailed process, inspired by…

Probability · Mathematics 2018-10-11 Olivier Durieu , Yizao Wang

The recently developed framework for quantum theory with no global causal order allows for quantum processes in which operations in local laboratories are neither causally ordered nor in a probabilistic mixture of definite causal orders.…

Quantum Physics · Physics 2016-09-21 Veronika Baumann , Časlav Brukner

For a class of piecewise deterministic Markov processes, the supports of the invariant measures are characterized. This is based on the analysis of controllability properties of an associated deterministic control system. Its invariant…

Dynamical Systems · Mathematics 2018-04-05 Michel Benaïm , Fritz Colonius , Lettau Ralph

The solution to a multivariate linear Stochastic Differential Equation (SDE) with constant initial state is well known to be a Gaussian Markov process, but its covariance kernel involves the solution to an integral equation in the general…

Probability · Mathematics 2016-05-10 Kerry Fendick

We consider a particle system with weights and the scaling limits derived from its occupation time. We let the particles perform independent recurrent L\'evy motions and we assume that their initial positions and weights are given by a…

Probability · Mathematics 2018-01-29 Łukasz Treszczotko

New index transforms, involving the real part of the modified Bessel function of the first kind as the kernel are considered. Mapping properties such as the boundedness and invertibility are investigated for these operators in the Lebesgue…

Classical Analysis and ODEs · Mathematics 2015-09-11 Semyon Yakubovich

We study the persistence probability for processes with stationary increments. Our results apply to a number of examples: sums of stationary correlated random variables whose scaling limit is fractional Brownian motion, random walks in…

Probability · Mathematics 2019-05-01 Frank Aurzada , Nadine Guillotin-Plantard , Françoise Pène