Fractional backward Kolmogorov equations

This paper derives the fractional backward Kolmogorov equations in fractal space-time based on the construction of a model for dynamic trajectories. It shows that for the type of fractional backward Kolmogorov equation in the fractal time whose coefficient functions are independent of time, its solution is equal to the transfer probability density function of the subordinated process X（Sα （t））, the subordinator Sα （t） is termed as the inverse-time a-stable subordinator and the process X（τ） satisfies the corresponding time homogeneous Ito stochastic differential equation.

Dynamics and Long Time Convergence of the Extended Fisher-Kolmogorov Equation under Numerical Discretization

We present a numerical study of the long time behavior of approxima- tion solution to the Extended Fisher-Kolmogorov equation with periodic boundary conditions. The unique solvability of numerical solution is shown. It is proved that there exists a global attractor of the discrete dynamical system. Furthermore, we obtain the long-time stability and convergence of the difference scheme and the upper semicontinuity d（Ah,τ, .A） → O. Our results show that the difference scheme can effectively simulate the infinite dimensional dynamical systems.

The Traveling Wave Solutions of Space-Time Fractional Partial Differential Equations by Modified Kudryashov Method

In this paper, the modified Kudryashov method is employed to find the traveling wave solutions of two well-known space-time fractional partial differential equations, namely the Zakharov Kuznetshov Benjamin Bona Mahony equation and Kolmogorov Petrovskii Piskunov equation, and as a helping tool, the sense of modified Riemann-Liouville derivative is also used. The propagation properties of obtained solutions are investigated where the graphical representations and justifications of the results are done by mathematical software Maple.

A new dynamic formula for determining the coefficient of Smagorinsky model

The most common method to determine the coefficient of Smagorinsky model now is to employ the Germano identity,however it is too complex and expensive in numerical calculation. In this letter we propose a new dynamic formula for determining the coefficient,which is based on the Kolmogorov equation of filtered velocity in physical space.The simplified formula is quite easy to implement in calculation.It is then verified in both homogeneous isotropic turbulence and wall-bounded turbulence by A Priori and A Posteriori tests.

Rational subgrid-scale modelling: a short survey

We review the previous attempts of rational subgrid-scale （SGS） modelling by employing theKolmogorov equation of filtered quantities. Aiming at explaining and solving the underlyingproblems in these models, we also introduce the recent methodological investigations for therational SGS modelling technique by defining the terms of assumption and restriction. Thesemethodological works are expected to provide instructive criterions for not only the rational SGSmodelling, but also other types of SGS modelling practices.

On Optimal Ordering of Service Parameters of a Coxian Queueing Model with Three Phases

We analyze a Coxian stochastic queueing model with three phases. The Kolmogorov equations of this model are constructed, and limit probabilities and the stationary probabilities of customer numbers in the system are found. The performance measures of this model are obtained and in addition the optimal order of service parameters is given with a theorem by obtaining the loss probabilities of customers in the system. That is, putting the greatest service parameter at first phase and the second greatest service parameter at second phase and the smallest service parameter at third phase makes the loss probability and means waiting time minimum. We also give the loss probability in terms of mean waiting time in the system. is the transition probability from j-th phase?to??phase . In this manner while and this system turns into queueing model and while the system turns into Cox(2) queueing model. In addition, loss probabilities are graphically given in a 3D graph for corresponding system parameters and phase transient probabilities. Finally it is shown with a numeric example that this theorem holds.

Equilibrium Arrivals to Preemptive Queueing System with Fixed and Random Population Size

A single-server queueing system with preemptive access is considered.Each customer has one attempt to enter the system at its working interval[0,T].As soon as the customer request enters the system,the server immediately starts the service.But when the next request arrives in the system,the previous one leaves the system even he has not finished his service yet.We study a non-cooperative game in which the customers wish to maximize their probability of obtaining service within a certain period of time.We characterize the Nash equilibrium and the price of anarchy,which is defined as the ratio between the optimal and equilibrium social utility.Two models are considered.In the first model the number of players is fixed,while in the second it is random and obeys the Poisson distribution.We demonstrate that there exists a unique symmetric equilibrium for both models.Finally,we calculate the price of anarchy for both models and show that the price of anarchy is not monotone with respect to the number of customers.

Numerical Solutions for Optimal Control of Stochastic Kolmogorov Systems

This work is concerned with controlled stochastic Kolmogorov systems.Such systems have received much attention recently owing to the wide range of applications in biology and ecology.Starting with the basic premise that the underlying system has an optimal control,this paper is devoted to designing numerical methods for approximation.Different from the existing literature on numerical methods for stochastic controls,the Kolmogorov systems take values in the first quadrant.That is,each component of the state is nonnegative.The work is designing an appropriate discrete-time controlled Markov chain to be in line with(locally consistent)the controlled diffusion.The authors demonstrate that the Kushner and Dupuis Markov chain approximation method still works.Convergence of the numerical scheme is proved under suitable conditions.

SECOND-ORDER NUMERICAL SCHEMES FOR DECOUPLED FORWARD-BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS WITH JUMPS

We propose new numerical schemes for decoupled forward-backward stochastic differ- ential equations （FBSDEs） with jumps, where the stochastic dynamics are driven by a d- dimensional Brownian motion and an independent compensated Poisson random measure. A semi-discrete scheme is developed for discrete time approximation, which is constituted by a classic scheme for the forward SDE [20, 28] and a novel scheme for the backward SDE. Under some reasonable regularity conditions, we prove that the semi-discrete scheme can achieve second-order convergence in approximating the FBSDEs of interest; and such convergence rate does not require jump-adapted temporal discretization. Next, to add in spatial discretization, a fully discrete scheme is developed by designing accurate quadrature rules for estimating the involved conditional mathematical expectations. Several numerical examples are given to illustrate the effectiveness and the high accuracy of the proposed schemes.

Estimation of 1-dimensional nonlinear stochastic differential equations based on higher-order partial differential equation numerical scheme and its application

A method based on higher-order partial differential equation （PDE） numerical scheme are proposed to obtain the transition cumulative distribution function （CDF） of the diffusion process （numerical differentiation of the transition CDF follows the transition probability density function （PDF））, where a transformation is applied to the Kolmogorov PDEs first, then a new type of PDEs with step function initial conditions and 0, 1 boundary conditions can be obtained. The new PDEs are solved by a fourth-order compact difference scheme and a compact difference scheme with extrapolation algorithm. After extrapolation, the compact difference scheme is extended to a scheme with sixth-order accuracy in space, where the convergence is proved. The results of the numericM tests show that the CDF approach based on the compact difference scheme to be more accurate than the other estimation methods considered; however, the CDF approach is not time-consuming. Moreover, the CDF approach is used to fit monthly data of the Federal funds rate between 1983 and 2000 by CKLS model.

Affine processes under parameter uncertainty

We develop a one-dimensional notion of affine processes under parameter uncertainty,which we call nonlinear affine processes.This is done as follows:given a setof parameters for the process,we construct a corresponding nonlinear expectation on the path space of continuous processes.By a general dynamic programming principle,we link this nonlinear expectation to a variational form of the Kolmogorov equation,where the generator of a single affine process is replaced by the supremum over all corresponding generators of affine processes with parameters in.This nonlinear affine process yields a tractable model for Knightian uncertainty,especially for modelling interest rates under ambiguity.We then develop an appropriate Ito formula,the respective term-structure equations,and study the nonlinear versions of the Vasiˇcek and the Cox–Ingersoll–Ross(CIR)model.Thereafter,we introduce the nonlinear Vasicek–CIR model.This model is particularly suitable for modelling interest rates when one does not want to restrict the state space a priori and hence this approach solves the modelling issue arising with negative interest rates.

Markov Jump Processes in Estimating Sharing of Identity by Descent

Identity by descent(IBD)sharing is a very important genomic feature in population genetics which can be used to reconstruct recent demographic history.In this paper we provide a framework to estimate IBD sharing for a demographic model called two-population model with migration.We adopt the structured coalescent theory and use a continuous-time Markov jump process{X(t),t≥0}to describe the genealogical process in such model.Then we apply Kolmogorov backward equation to calculate the distribution of coalescence time and develop a formula for estimating the IBD sharing.The simulation studies show that our method to estimate IBD sharing for this demographic model is robust and accurate.

Dynamic Evasion-Interrogation Games with Uncertainty in the Context of Electromagetics

We consider two player electromagnetic evasion-pursuit games where each player must incorporate significant uncertainty into their design strategies to disguise their intension and confuse their opponent.In this paper,the evader is allowed to make dynamic changes to his strategies in response to the dynamic input with uncertainty from the interrogator.The problem is formulated in two different ways;one is based on the evolution of the probability density function of the intensity of reflected signal and leads to a controlled forward Kolmogorov or Fokker-Planck equation.The other formulation is based on the evolution of expected value of the intensity of reflected signal and leads to controlled backward Kolmogorov equations.In addition,a number of numerical results are presented to illustrate the usefulness of the proposed approach in exploring problems of control in a general dynamic game setting.

Stochastic Optimal Control for First-Passage Failure of Nonlinear Oscillators with Multi-Degrees-of-Freedom

To enhance the reliability of the stochastically excited structure,it is significant to study the problem of stochastic optimal control for minimizing first-passage failure.Combining the stochastic averaging method with dynamical programming principle,we study the optimal control for minimizing first-passage failure of multidegrees-of-freedom(MDoF)nonlinear oscillators under Gaussian white noise excitations.The equations of motion of the controlled system are reduced to time homogenous difusion processes by stochastic averaging.The optimal control law is determined by the dynamical programming equations and the control constraint.The backward Kolmogorov(BK)equation and the Pontryagin equation are established to obtain the conditional reliability function and mean first-passage time(MFPT)of the optimally controlled system,respectively.An example has shown that the proposed control strategy can increase the reliability and MFPT of the original system,and the mathematical treatment is also facilitated.