Time-space fractional stochastic Ginzburg-Landau equation driven by Gaussian white noise

The current article is devoted to the time-spatial regularity of the nonlocal stochastic convolution for Caputo-type time fractional nonlocal Ornstein-Ulenbeck equations. The dependence of the order of time-fractional derivative, the order of the space-fractional derivative, and the regularity of the initial data are revealed. The global existence and uniqueness of the mild solutions for time-space fractional complex Ginzburg-Landau equation driven by Gaussian white noise are established.     

Analysis of bifurcations for non-linear stochastic non-smooth vibro-impact system via top Lyapunov exponent

Bifurcations are discussed by the criterion of top Lyapunov exponent. Based on the local map and Kaminski’s algorithms, a general formulation of the top Lyapunov exponents is proposed for non-linear vibro-impact oscillators with Gaussian white noise perturbation. The analytical results are verified by phase portraits and bifurcation diagrams for a classical stochastic Duffing vibro-impact oscillator. Both results are consistent.     

Primary resonance of Duffing oscillator with fractional-order derivative

In this paper the primary resonance of Duffing oscillator with fractional-order derivative is researched by the averaging method. At first the approximately analytical solution and the amplitude-frequency equation are obtained. Additionally, the effect of the fractional-order derivative on the system dynamics is analyzed, and it is found that the fractional-order derivative could affect not only the viscous damping, but also the linear stiffness, which is characterized by the equivalent damping coefficient and the equivalent stiffness coefficient. This conclusion is remarkably different from the existing research results about nonlinear system with fractional-order derivative. Moreover, the comparisons of the amplitude-frequency curves by the approximately analytical solution and the numerical integration are fulfilled, and the results certify the correctness and satisfactory precision of the approximately analytical solution. At last, the effects of the two parameters of the fractional-order derivative, i.e. the fractional coefficient and the fractional order, on the amplitude-frequency curves are investigated, which are different from the traditional integer-order Duffing oscillator.     

On the stochastic response of a fractionally-damped Duffing oscillator

A numerical method is presented to compute the response of a viscoelastic Duffing oscillator with fractional derivative damping, subjected to a stochastic input. The key idea involves an appropriate discretization of the fractional derivative, based on a preliminary change of variable, that allows to approximate the original system by an equivalent system with additional degrees of freedom, the number of which depends on the discretization of the fractional derivative. Unlike the original system that, due to the presence of the fractional derivative, is governed by non-ordinary differential equations, the equivalent system is governed by ordinary differential equations that can be readily handled by standard integration methods such as the Runge–Kutta method. In this manner, a significant reduction of computational effort is achieved with respect to the classical solution methods, where the fractional derivative is reverted to a Grunwald–Letnikov series expansion and numerical integration methods are applied in incremental form. The method applies for fractional damping of arbitrary order α (0 < α < 1) and yields very satisfactory results. With respect to its applications, it is worth remarking that the method may be considered for evaluating the dynamic response of a structural system under stochastic excitations such as earthquake and wind, or of a motorcycle equipped with viscoelastic devices on a stochastic road ground profile.     

Noise-induced vegetation transitions in the Grazing Ecosystem

The Grazing Ecosystem is a special case of predator-prey systems, which has attracted widespread attention since a long time ago. Because of the ubiquity of noise, there is a growing need to research the influences of noise on the Grazing Ecosystem. This paper is devoted to investigating the transition behaviors of the high vegetation biomass in the Grazing Ecosystem subjected to Gaussian noise and Lévy noise, respectively. Firstly, the original system is translated into the Itô stochastic differential equation, which is utilized to derive the analytical expression of the escape probability through the Dirichlet boundary value problems. Then the transitions between the two vegetation potential wells are explored by calculating the size of the stochastic basin of attraction based on the escape probability. The comparison between the analytical results and the ones through Monte Carlo simulations shows that the proposed method works very well. It turns out that the Gaussian white noise intensity, Lévy noise stability parameter and herbivore density have different impact mechanisms on the basin stability of high density vegetation in the stochastic Grazing Ecosystem.     

Fractionalization of the complex-valued Brownian motion of order n using Riemann–Liouville derivative. Applications to mathematical finance and stochastic mechanics

The (complex-valued) Brownian motion of order n is defined as the limit of a random walk on the complex roots of the unity. Real-valued fractional noises are obtained as fractional derivatives of the Gaussian white noise (or order two). Here one combines these two approaches and one considers the new class of fractional noises obtained as fractional derivative of the complex-valued Brownian motion of order n. The key of the approach is the relation between differential and fractional differential provided by the fractional Taylor’s series of analytic function , where E is the Mittag–Leffler function on the one hand, and the generalized Maruyama’s notation, on the other hand. Some questions are revisited such as the definition of fractional Brownian motion as integral w.r.t. (dt), and the exponential growth equation driven by fractional Brownian motion, to which a new solution is proposed. As a first illustrative example of application, in mathematical finance, one proposes a new approach to the optimal management of a stochastic portfolio of fractional order via the Lagrange variational technique applied to the state moment dynamical equations. In the second example, one deals with non-random Lagrangian mechanics of fractional order. The last example proposes a new approach to fractional stochastic mechanics, and the solution so obtained gives rise to the question as to whether physical systems would not have their own internal random times.     

Regularity of Ornstein–Uhlenbeck Processes Driven by a Lévy White Noise

The paper is concerned with spatial and time regularity of solutions to linear stochastic evolution equation perturbed by Lévy white noise “obtained by subordination of a Gaussian white noise”. Sufficient conditions for spatial continuity are derived. It is also shown that solutions do not have in general cádlág modifications. General results are applied to equations with fractional Laplacian. Applications to Burgers stochastic equations are considered as well.     

On generalized Malliavin calculus

The Malliavin derivative, the divergence operator (Skorokhod integral), and the Ornstein-Uhlenbeck operator are extended from the traditional Gaussian setting to nonlinear generalized functionals of white noise. These extensions are related to the new developments in the theory of stochastic PDEs, in particular elliptic PDEs driven by spatial white noise and quantized nonlinear equations.     

Principal resonance responses of SDOF systems with small fractional derivative damping under narrow-band random parametric excitation

The principal resonance responses of nonlinear single-degree-of-freedom (SDOF) systems with lightly fractional derivative damping of order α (0 < α < 1) subject to the narrow-band random parametric excitation are investigated. The method of multiple scales is developed to derive two first order stochastic differential equation of amplitude and phase, and then to examine the influences of fractional order and intensity of random excitation on the first-order and second-order moment. As an example, the stochastic Duffing oscillator with fractional derivative damping is considered. The effects of detuning frequency parameter, the intensity of random excitation and the fractional order derivative damping on stability are studied through the largest Lyapunov exponent. The corresponding theoretical results are well verified through direct numerical simulations. In addition, the phenomenon of stochastic jump is analyzed for parametric principal resonance responses via finite differential method. The stochastic jump phenomena indicates that the most probable motion is around the larger non-trivial branch of the amplitude response when the intensity of excitation is very small, and the probable motion of amplitude responses will move from the larger non-trivial branch to trivial branch with the increasing of the intensity of excitation. Such stochastic jump can be considered as bifurcation.     

Stochastic realization of a Gaussian stochastic control system

The stochastic realization problem is considered of representing a stationary Gaussian process as the observation process of a Gaussian stochastic control system. The problem formulation includes that the lastm components of the observation process form the Gaussian white noise input process to the system. Identifiability of this class of systems motivates the problem. The results include a necessary and sufficient condition for the existence of a stochastic realization. A subclass of Gaussian stochastic control systems is defined that is almost a canonical form for this stochastic realization problem. For a structured Gaussian stochastic control system an equivalent condition for identifiability of the parametrization is stated.The research of this paper is supported in part by the Commission of the European Communities through the SCIENCE Program by the projectSystem Identification with contract number SC1-CT92-0779.     

Path integral for the probability of the trajectories generated by fractional dynamics subject to Gaussian white noise

One considers a fractional stochastic process defined as the dynamics of a non-random fractional system subject to a Gaussian white noise. One shows how the probability distribution of the random paths so generated can be obtained by combining path integrals and the maximum entropy principle.     

Noise-induced chaos and basin erosion in softening Duffing oscillator

It is common for many dynamical systems to have two or more attractors coexist and in such cases the basin boundary is fractal. The purpose of this paper is to study the noise-induced chaos and discuss the effect of noises on erosion of safe basin in the softening Duffing oscillator. The Melnikov approach is used to obtain the necessary condition for the rising of chaos, and the largest Lyapunov exponent is computed to identify the chaotic nature of the sample time series from the system. According to the Melnikov condition, the safe basins are simulated for both the deterministic and the stochastic cases of the system. It is shown that the external Gaussian white noise excitation is robust for inducing the chaos, while the external bounded noise is weak. Moreover, the erosion of the safe basin can be aggravated by both the Gaussian white and the bounded noise excitations, and fractal boundary can appear when the system is only excited by the random processes, which means noise-induced chaotic response is induced.     

Time fractional and space nonlocal stochastic nonlinear Schrödinger equation driven by Gaussian white noise

We present the time-spatial regularity of the nonlocal stochastic convolution for Caputo-type time fractional nonlocal Ornstein–Ulenbeck equations by the generalized Mittag–Leffler functions and Mainardi function, and establish the existence and uniqueness of mild solutions for time fractional and space nonlocal stochastic nonlinear Schrödinger equation driven by Gaussian white noise. In addition, the global mild solution is also shown.     

Existence and Smoothness of the Density for Spatially Homogeneous SPDEs

In this paper, we extend Walsh’s stochastic integral with respect to a Gaussian noise, white in time and with some homogeneous spatial correlation, in order to be able to integrate some random measure-valued processes. This extension turns out to be equivalent to Dalang’s one. Then we study existence and regularity of the density of the probability law for the real-valued mild solution to a general second order stochastic partial differential equation driven by such a noise. For this, we apply the techniques of the Malliavin calculus. Our results apply to the case of the stochastic heat equation in any space dimension and the stochastic wave equation in space dimension d=1,2,3. Moreover, for these particular examples, known results in the literature have been improved.      

On the Equivalence of Multiparameter Gaussian Processes

Our purpose is to characterize the multiparameter Gaussian processes, that is Gaussian sheets, that are equivalent in law to the Brownian sheet and to the fractional Brownian sheet. We survey multiparameter analogues of the Hitsuda, Girsanov and Shepp representations. As an application, we study a special type of stochastic equation with linear noise.      

On the solutions of nonlinear stochastic fractional partial differential equations in one spatial dimension

Existence, uniqueness and regularity of the trajectories of mild solutions of one-dimensional nonlinear stochastic fractional partial differential equations of order $\alpha >1$ containing derivatives of entire order and perturbed by space–time white noise are studied. The fractional derivative operator is defined by means of a generalized Riesz–Feller potential.     

随机Hamilton系统同胚流的大偏差原理

在非Lipschitz条件下得到随机微分方程同胚流的大偏差原理.作为应用,本文同时给出了随机Hamilton系统同胚流的大偏差原理.特别地,以下二阶非线性随机振荡方程同胚流的大偏差原理也同样成立:Z_t=C_0Z_t-Z_t~3+Θ(Z_t)W_t,(Z_0,Z_0)=(z,u)∈R~2,其中C_0为任意常数,Θ为一阶导数有界的二阶连续可微函数,W_t是一维Brown白噪声.     

Oscillatory region and asymptotic solution of fractional van der Pol oscillator via residue harmonic balance technique

In this paper, a powerfully analytical technique is proposed for predicting and generating the steady state solution of the fractional differential system based on the method of harmonic balance. The zeroth-order approximation using just one Fourier term is applied to predict the parametric function for the boundary between oscillatory and non-oscillatory regions of the fractional van der Pol oscillator. The unbalanced residues due to Fourier truncation are considered iteratively by solving linear algebraic equations to improve the accuracy of the solutions successively. The highly accurate solutions to the angular frequency and limit cycle of fractional van der Pol oscillator are obtained and compared. The results reveal that the technique described in this paper is very effective and simple for obtaining asymptotic solution of nonlinear system having fractional order derivative.     

Stochastic optimal time-delay control of quasi-integrable Hamiltonian systems

A nonlinear stochastic optimal time-delay control strategy for quasi-integrable Hamiltonian systems is proposed. First, a stochastic optimal control problem of quasi-integrable Hamiltonian system with time-delay in feedback control subjected to Gaussian white noise is formulated. Then, the time-delayed feedback control forces are approximated by the control forces without time-delay and the original problem is converted into a stochastic optimal control problem without time-delay. After that, the converted stochastic optimal control problem is solved by applying the stochastic averaging method and the stochastic dynamical programming principle. As an example, the stochastic time-delay optimal control of two coupled van der Pol oscillators under stochastic excitation is worked out in detail to illustrate the procedure and effectiveness of the proposed control strategy.     

Chaos expansion methods of stochastic processes for Malliavin-type equations

In this short survey we present the application of the Askey-scheme of orthogonal polynomials to define several discrete and continuous distribution types in frame-work of T. Hidaʼs white noise analysis. The results are applied to define fractional versions of the distributions and to solve stochastic differential equations involving the Malliavin derivative, Skorokhod integral and Ornstein-Uhlenbeck operator.