On the local dynamics of polynomial difference equations with fading stochastic perturbations

We examine the stability-instability behaviour of a polynomial difference equa- tion with state-independent, asymptotically fading stochastic perturbations. We find that the set of initial values can be partitioned into a stability region, an instability region, and a region of unknown dynamics that is in some sense \small". In the ¯rst two cases, the dynamic holds with probability at least 1 ¡ °, a value corresponding to the statistical notion of a confidence level. Aspects of an equation with state-dependent perturbations are also treated. When the perturbations are Gaussian, the difference equation is the Euler-Maruyama dis- cretisation of an It^o-type stochastic differential equation with solutions displaying global a.s. asymptotic stability. The behaviour of any particular solution of the difference equation can be made consistent with the corresponding solution of the differential equation, with probability 1 ¡ °, by choosing the stepsize parameter sufficiently small. We present examples illustrating the relationship between h, ° and the size of the stability region

Some stability theorems for ordinary difference equations

Stability theorems using invariance properties of difference equation solution

Bohl-Perron type stability theorems for linear difference equations with infinite delay

Relation between two properties of linear difference equations with infinite delay is investigated: (i) exponential stability, (ii) \l^p-input \l^q-state stability (sometimes is called Perron's property). The latter means that solutions of the non-homogeneous equation with zero initial data belong to \l^q when non-homogeneous terms are in \l^p. It is assumed that at each moment the prehistory (the sequence of preceding states) belongs to some weighted \l^r-space with an exponentially fading weight (the phase space). Our main result states that (i) $\Leftrightarrow$ (ii) whenever $(p,q) \neq (1,\infty)$ and a certain boundedness condition on coefficients is fulfilled. This condition is sharp and ensures that, to some extent, exponential and \l^p-input \l^q-state stabilities does not depend on the choice of a phase space and parameters $p$ and $q$, respectively. \l^1-input \l^\infty-state stability corresponds to uniform stability. We provide some evidence that similar criteria should not be expected for non-fading memory spaces.Comment: To be published in Journal of Difference Equations and Application

Nash Equilibrium and Robust Stability in Dynamic Games: A Small-Gain Perspective

This paper develops a novel methodology to study robust stability properties of Nash equilibrium points in dynamic games. Small-gain techniques in modern mathematical control theory are used for the first time to derive conditions guaranteeing uniqueness and global asymptotic stability of Nash equilibrium point for economic models described by functional difference equations. Specification to a Cournot oligopoly game is studied in detail to demonstrate the power of the proposed methodology.Dynamic game; Cournot oligopoly; Nash equilibrium; Robust stability; Small gain

Difference Methods and Deferred Corrections for Ordinary Boundary Value Problems

Compact as possible difference schemes for systems of nth order equations are developed. Generalizations of the Mehrstellenverfahren and simple theoretically sound implementations of deferred corrections are given. It is shown that higher order systems are more efficiently solved as given rather than as reduced to larger lower order systems. Tables of coefficients to implement these methods are included and have been derived using symbolic computations

Mimetic Finite Difference methods for Hamiltonian wave equations in 2D

In this paper we consider the numerical solution of the Hamiltonian wave equation in two spatial dimension. We use the Mimetic Finite Difference (MFD) method to approximate the continuous problem combined with a symplectic integration in time to integrate the semi-discrete Hamiltonian system. The main characteristic of MFD methods, when applied to stationary problems, is to mimic important properties of the continuous system. This approach, associated with a symplectic method for the time integration yields a full numerical procedure suitable to integrate Hamiltonian problems. A complete theoretical analysis of the method and some numerical simulations are developed in the paper.Comment: 26 pages, 8 figure

Convergence and stability of finite difference schemes for some elliptic equations

The problem of convergence and stability of finite difference schemes used for solving boundary value problems for some elliptic partial differential equations has been studied in this thesis. Generally a boundary value problem is first replaced by a discretized problem whose solution is then found by numerical computation. The difference between the solution of the discretized problem and the exact solution of the boundary value problem is called the discretization error. This error is a measure of the accuracy of the numerical solution, provided the roundoff error is negligible. Estimates of the discretization error are obtained for a class of elliptic partial differential equations of order 2m (M ≥ 1) with constant coefficients in a general n-dimensional domain. This result can be used to define finite difference approximations with an arbitrary order of accuracy. The numerical solution of a discretized problem is usually obtained by solving the resulting system of algebraic equations by some iterative procedure. Such a procedure must be stable in order to yield a numerical solution. The stability of such an iteration scheme is studied in a general setting and several sufficient con­ditions of stability are obtained. When a higher order differential equation is solved numeri­cally, roundoff error can accumulate during the computations. In order to reduce this error the differential equation is sometimes replaced by several lower order differential equations. The method of splitting is analyzed for the two-dimensional biharmonic equation and the convergence of the discrete solution to the exact solution is discussed. An iterative procedure is presented for obtaining the numerical solution. It is shown that this method is also applicable to non-rectangular domains. The accuracy of numerical solutions of a nonselfadjoint elliptic differential equation is discussed when it is solved with a finite non-zero mesh size. This equation contains a parameter which may take large values. Some extensions to the two-dimensional Navier-Stokes equations are also presented

On the stability of linear stochastic difference equations

We study the discrete time stochastic system on IR[subscript]sp0 d, x[subscript] n + 1 = A ([xi][subscript] n) x[subscript] n, where (with further specifications given in the text) [xi][subscript] n is a Feller stationary ergodic Markov chain taking values on a connected C[superscript][infinity] Riemannian manifold W and A is a mapping from W into Gl (d, IR).;This investigation is performed via the tools of geometric control theory and Lyapunov exponents. The two main results are: (1) Under some assumptions to be specified, the Markov chain (x[subscript] n, [xi][subscript] n) possesses a unique invariant (probability) measure. (2) Using the existence of this unique invariant probability measure, the Lyapunov exponent associated with this stochastic system is almost surely unique and independent of the intial value.;This last result is used to initiate a study of the asymptotic stability behavior of the sytem, using both Lyapunov and moment Lyapunov exponents.;To illustrate the above, a computer simulation is performed on a discretized version of the linear oscillator with damping and restoring force.;As it is the case for similar studies on continuous time systems, one of the assumptions required to obtain the above results amounts to a Lie algebra condition on some collection of vector fields arising from the dynamics of the system