The existence and asymptotic estimations of solutions to stochastic pantograph equations with diffusion and Lévy jumps

In this paper, we consider a class of stochastic pantograph differential equations with Lévy jumps (SPDEwLJs). By using the Burkholder-Davis-Gundy inequality and the Kunita's inequality, we prove the existence and uniqueness of solutions to SPDEwLJs whose coefficients satisfying the Lipschitz conditions and the local Lipschitz conditions. Meantime, we establish the p-th exponential estimations and almost surely asymptotic estimations of solutions to SPDEwLJs

An averaging principle for neutral stochastic functional differential equations driven by Poisson random measure

In this paper, we study the averaging principle for neutral stochastic functional differential equations (SFDEs) with Poisson random measure. By stochastic inequality, Burkholder-Davis-Gundy’s inequality and Kunita’s inequality, we prove that the solution of the averaged neutral SFDEs with Poisson random measure converges to that of the standard one in (Formula presented.) sense and also in probability. Some illustrative examples are presented to demonstrate this theory

Stability of stochastic differential equations in infinite dimensions

In engineering, physics and economics, many dynamical systems involving with stochastic components and random noise are often modeled by stochastic models. The stochastic effects of these models are often used to describe the uncertainty about the operating systems. Motivated by the development of analysis and theory of stochastic processes, as well as the studies of natural sciences, the theory of stochastic differential equations in infinite dimensional spaces evolves gradually into a branch of modern analysis. Many qualitative properties of such systems have been studied in the past few decades, among which, investigation of stability of such systems is often regarded as the first characteristic of the dynamical systems or models. In general, this thesis is mainly concerned with the studies of the stability property of stochastic differential equations in Hilbert spaces. Chapter 1 is an introduction to a brief history of stochastic differential equations in infinite dimensions, together with an overview of the studies. Chapter 2 is a presentation of preliminaries to some basic stochastic analysis. In Chapter 3, we study the stability in distribution of mild solutions to stochastic delay differential equations with Poisson jumps. Firstly, we use approximation of strong solutions to pass on the stability of strong solutions to the mild ones. Then, by constructing a suitable metric between the transition probability functions of mild solutions, we obtain the desired stability result under some suitable conditions. In Chapter 4, we investigate the stochastic partial delay differential equations with Markovian switching and Poisson jumps. By estimating the coefficients of energy equality, both the exponential stability and almost sure exponential stability of energy solutions to the equations are obtained. In Chapter 5, we study the relationship among strong, weak and mild solutions to the stochastic functional differential equations of neutral type. Finally, in Chapter 6, we study the asymptotic stability of two types of equations, impulsive stochastic delay differential equations with Poisson jumps and stochastic evolution equations with Poisson jumps. By employing the fixed point theorem, we derive the desired stability results under some criteria

Balancing Related Model Order Reduction Applied to Linear Controlled Evolution Equations with Lévy Noise

Otto-von-Guericke-Universität Magdeburg, Fakultät für Mathematik, Dissertation, 2016von Martin Redmann, M. Sc.Literaturverzeichnis: Blatt 177-18

Una contribución al análisis de las ecuaciones en derivadas parciales estocásticas funcionales con derivadas fraccionarias en tiempo y aplicaciones

On the one hand, the classical heat equation∂tu= ∆udescribes heatpropagation in a homogeneous medium, while the time fractional diffusionequation∂αtu= ∆uwith 0< α <1 has been widely used to model anoma-lous diffusion exhibiting subdiffusive behavior. On the other side, when weconsider a physical system in the real world, we have to consider some in-fluences of internal, external, or environmental noises. Besides, the wholebackground of physical system may be difficult to describe deterministical-ly. Therefore, in this thesis, we will construct three models to show theapplications of the time fractional stochastic functional partial differentialequations.In Chapter 2, we study a stochastic lattice system with Caputo fractionalsubstantial time derivative, the asymptotic behavior of this kind of problemis investigated. In particular, the existence of a global forward attractingset in the weak mean-square topology is established. A general theorem onthe existence of solutions for a fractional SDE in a Hilbert space under theassumption that the nonlinear term is weakly continuous in a given sense isestablished and applied to the lattice system. The existence and uniquenessof solutions for a more general fractional SDEs is also obtained under aLipschitz condition.In Chapter 3, the local and global existence and uniqueness of mild solu-tions to a kind of stochastic time fractional impulsive differential equationsare studied by means of a fixed point theorem, and with the help of theproperty ofα-order fractional solution operatorTα(t) and the resolvent op-eratorSα(t). Moreover, the exponential decay to zero of the mild solutionsto this model is also proved. However, the lack of compactness of theα-order resolvent operatorSα(t) does not allow us to establish the existenceand structure of attracting sets, which is a key concept for understandingthe dynamical properties.Therefore, the second model of Chapter 3 is concerned with the well-posedness and dynamics of delay impulsive fractional stochastic evolutionequations with time fractional differential operatorα∈(0,1). After estab-lishing the well-posedness of the problem, and a result ensuring the existenceand uniqueness of mild solutions globally defined in future, the existence ofa minimal global attracting set is investigated in the mean-square topology,under general assumptions not ensuing the uniqueness of solutions. Further-more, in the case of uniqueness, it is possible to provide more informationabout the geometrical structure of such global attracting set. In particular,it is proved that the minimal compact globally attracting set for the solution-1 s of the problem becomes a singleton. It is remarkable that the attractionproperty is proved in the usual forward sense, unlike the pullback conceptused in the context of random dynamical systems, but the main point is thatthe model under study has not been proved to generate a random dynamicalsystem.Chapter 4 is devoted to the well-posedness of stochastic time fractional2D-Stokes equations of orderα∈(0,1) containing finite or infinite delay withmultiplicative noise is established, respectively, in the spacesC([−h,0];L2(Ω);L2σ)) andC((−∞,0];L2(Ω;L2σ)). The existence and uniqueness of mild so-lution to such kind of equations are proved by using a fixed-point argument.Also the continuity with respect to initial data is shown. Finally, we con-clude with several comments on future research concerning the challengingmodel: time fractional stochastic delay 2D-Navier-Stokes equations withmultiplicative noise

Modeling of volatility-linked financial products

This thesis is the collation of four papers, adapted from their original versions as to form here four distinct chapters. In the first chapter we illustrate and solve the pricing problem of a target volatility option (TVO) using three different methodologies. In the second chapter we study the pricing PDE for a general contingent claim involving an asset and its realized volatility, and then solve it for a variety of actual models and payoffs. The third chapter introduces a class of time-changed stochastic processes based on which a martingale asset price evolution can be devised. Pricing equations for volatility-linked derivatives are also obtained in this framework. In the final chapter we analyze one specific model of this class; we conclude that it does show high flexibility in explaining the forward volatility skew dynamics and that it can capture certain interesting stylized facts

Models of Delay Differential Equations

This book gathers a number of selected contributions aimed at providing a balanced picture of the main research lines in the realm of delay differential equations and their applications to mathematical modelling. The contributions have been carefully selected so that they cover interesting theoretical and practical analysis performed in the deterministic and the stochastic settings. The reader will find a complete overview of recent advances in ordinary and partial delay differential equations with applications in other multidisciplinary areas such as Finance, Epidemiology or Engineerin

Uncertainty Quantification in Image Segmentation Using the Ambrosio–Tortorelli Approximation of the Mumford–Shah Energy

The quantification of uncertainties in image segmentation based on the Mumford–Shah model is studied. The aim is to address the error propagation of noise and other error types in the original image to the restoration result and especially the reconstructed edges (sharp image contrasts). Analytically, we rely on the Ambrosio–Tortorelli approximation and discuss the existence of measurable selections of its solutions as well as sampling-based methods and the limitations of other popular methods. Numerical examples illustrate the theoretical findings