Evaluation of integrals by decomposition

It is shown that in addition to its advantages for nonlinear and/or stochastic differential equations [1,2], the decomposition method may be preferable even for equations, such as linear deterministic ordinary differential equations which are easily solvable by well-known methods in integral form because the evaluations of the integrals is easier. It is also shown that since solutions of differential equations are easily obtained by decomposition, it can be convenient to change a difficult integration problem to an easily solved differential equation and consequently evaluate the integral in an easily computed convergent series.     

Adomian decomposition method for solution of differential-algebraic equations

Solutions of differential algebraic equations is considered by Adomian decomposition method. In E. Babolian, M.M. Hosseini [Reducing index and spectral methods for differential-algebraic equations, J. Appl. Math. Comput. 140 (2003) 77] and M.M. Hosseini [An index reduction method for linear Hessenberg systems, J. Appl. Math. Comput., in press], an efficient technique to reduce index of semi-explicit differential algebraic equations has been presented. In this paper, Adomian decomposition method is applied to reduced index problems. The scheme is tested for some examples and the results demonstrate reliability and efficiency of the proposed methods.     

Regularity properties of a class of hybrid methods

IntroductionIt is important that the discrete dynamical system given by a numerical method appliedto a continuous dynamical system can have the same dynamical properties as the underlyingcontinuous system. Recently, many authors[1--71 have investigated the conditions under whichspurious solutions are not introduced by time discretization, and many interesting results aboutRunge-Kutta methods, linear multistep methods and general linear methods applied to dynamical systems of ordinary different…     

Constructive methods for certain Bergman operators

This paper is concerned with the class of linear partial differential equations of second order such that there exist Bergman operators with polynomial kernels (cf, [12]). In an earlier paper [ll] the authors have shown that these equations also admit differential operators as introduced by K. W. Bauer [I]. In the present paper, relations between different types of representations of solutions are investigated. These representations are of interest in developing a function theory of solutions; cf., for instance, K. W. Bauer [I] and S. Ruscheweyh [19]. They are also essential to global extensions of local results obtained by means of Bergman operators of the first kind. The inversion problem for those operators is solved, and it is shown that all solutions of equations of that class which are holomorphic in a domain of C² can be represented by operators with polynomial kernels. Furthermore, a construction principle for deriving the equations investigated by K. W. Bauer [2] is obtained; this yields corresponding representations of solutions by differential and integral operators in a systematic fashion     

Numerical approach to differential equations of fractional order

In this paper, the variational iteration method and the Adomian decomposition method are implemented to give approximate solutions for linear and nonlinear systems of differential equations of fractional order. The two methods in applied mathematics can be used as alternative methods for obtaining analytic and approximate solutions for different types of differential equations. In these schemes, the solution takes the form of a convergent series with easily computable components. This paper presents a numerical comparison between the two methods for solving systems of fractional differential equations. Numerical results show that the two approaches are easy to implement and accurate when applied to differential equations of fractional order.     

A parallel four step domain decomposition scheme for coupled forward–backward stochastic differential equations

Motivated by the idea of imposing paralleling computing on solving stochastic differential equations (SDEs), we introduce a new domain decomposition scheme to solve forward–backward stochastic differential equations (FBSDEs) parallel. We reconstruct the four step scheme in Ma et al. (1994) [1] and then associate it with the idea of domain decomposition methods. We also introduce a new technique to prove the convergence of domain decomposition methods for systems of quasilinear parabolic equations and use it to prove the convergence of our scheme for the FBSDEs.     

A hybrid approach to 3-level FETI

Finite Element Tearing and Interconnecting (FETI) methods are nonoverlapping domain decomposition methods which have been proven to be very robust and parallel scalable for a class of elliptic partial differential equations. These methods are also called dual domain decomposition methods since the continuity accross the subdomain boundaries is enforced by Lagrange multipliers and, after elimination of the primal variables, the remaining Schur complement system is solved iteratively in the Lagrange multiplier space using a Krylov space method. Domain decomposition methods iterating on the primal variables are called primal substructuring methods. FETI and FETI–DP methods are different members of the family of dual domain decomposition methods. Their standard versions have in common that the local subproblems and a small global problem are solved exactly by a direct method, essentially representing two different levels within the algorithm. Several extensions of dual and primal iterative substructuring beyond two levels have been proposed in the past, see, e.g., [7] for FETI–DP, and, e.g., Tu [13,12,11] or [9] and [1] for BDDC. In the present article, a hybrid FETI/FETI–DP method is considered and some numerical results are presented. It is noted that independently, there is ongoing research on hybrid FETI methods by Jungho Lee of the Courant Institute. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

高阶非线性中立型方程正解的渐近性及存在性

本文利用非线性分析中半序方法和增算子不动点定理，对高阶非线性中立型方程正解的渐近性进行了详细分类，并且给出了各种类型正解存在的充要条件和具体例子．     

任意体上的双矩阵分解与矩阵方程

本文给出了任意体上具有相同行数或相同列数的双矩阵分解定理；利用此定理，给出了任意体上的矩阵方程ＡＸＢ＋ＣＹＤ＝Ｅ及［Ａ１ＸＢ１，Ａ２ＸＢ２］＝［Ｅ１；Ｅ２］有解的充要条件及其一般解的表达式．     

Numerical detection and study of singularities in solutions of differential equations

New simple and robust methods are proposed for detecting singularities, such as poles, logarithmic poles, and mixed singularities, in systems of ordinary differential equations. The methods produce characteristics of these singularities with an a posteriori asymptotically precise error estimate. They are applicable in the case of an arbitrary parametrization of integral curves, including one in terms of the arc length, which is optimal for stiff and ill-conditioned problems. Following this approach, blowup solutions can be detected for a broad class of important nonlinear partial differential equations, since they are reducible by the method of lines to systems of ordinary differential equations of huge orders. The simplicity and reliability of the approach are superior to those of previously known methods.     

A note on the use of Adomian decomposition method for high-order and system of nonlinear differential equations

This paper extends an earlier work [Hosseini MM, Nasabzadeh H. Modified Adomian decomposition method for specific second order ordinary differential equations. Appl Math Comput 2007;186:117–23] to high order and system of differential equations. Solution of these problems is considered by proposed modification of Adomian decomposition method. Furthermore, with providing some examples, the aforementioned cases are dealt with numerically.     

Integrating first-order differential equations with Liouvillian solutions via quadratures: a semi-algorithmic method

Here we present a semi-algorithmic method to deal with rational first-order ordinary differential equations, with Liouvillian solutions. This method is based on the knowledge of the general structure for the integrating factor for such equations.     

Convergent series solution of nonlinear equations

The author's decomposition method [1] provides a new, efficient computational procedure for solving large classes of nonlinear (and/or stochastic) equations. These include differential equations containing polynomial, exponential, and trigonometric terms, negative or irrational powers, and product nonlinearities [2]. Also included are partial differential equations [3], delay-differential equations [4], algebraic equations [5], and matrix equations [6] which describe physical systems. Essentially the method provides a systematic computational procedure for equations containing any nonlinear terms of physical significance. The procedure depends on calculation of the author's A_n, a finite set of polynomials [1,13] in terms of which the nonlinearities can be expressed. This paper shows important properties of the A_n which ensure an accurate and computable convergent solution by the author's decomposition method [1]. Since the nonlinearities and/or stochasticity which can be handled are quite general, the results are potentially extremely useful for applications and make a number of common approximations such as linearization, unnecessary.     

Numerical methods for nonlinear partial differential equations of fractional order

In this article, we implement relatively new analytical techniques, the variational iteration method and the Adomian decomposition method, for solving nonlinear partial differential equations of fractional order. The fractional derivatives are described in the Caputo sense. The two methods in applied mathematics can be used as alternative methods for obtaining analytic and approximate solutions for different types of fractional differential equations. In these schemes, the solution takes the form of a convergent series with easily computable components. Numerical results show that the two approaches are easy to implement and accurate when applied to partial differential equations of fractional order.     

Finding exact solutions of nonlinear PDEs using the natural decomposition method

In this work, we implement the natural decomposition method (NDM) to solve nonlinear partial differential equations. We apply the NDM to obtain exact solutions for three applications of nonlinear partial differential equations. The new method is a combination of the natural transform method and the Adomian decomposition method. We prove some of the properties that are related to the natural transform method. The results are compared with existing solutions obtained by other methods, and one can conclude that the NDM is easy to use and efficient. Copyright © 2016 John Wiley & Sons, Ltd.     

关于具有转向点的一类常微分方程的边值问题

本文应用多重尺度法研究具有转向点的一类常微分方程的边值问题.避免了[1]中出现的悖理,以及[2]中关于确定任意常数的变分运算;构造出边值问题的解的一致有效渐近近似式.并研究了非共振的情形.     

Necessary conditions and a test for the stability of a system of two linear ordinary differential equations of the first order

We use the Riccati equation method for the derivation of necessary conditions and a test for the stability of a system of two linear first-order ordinary differential equations. We consider an example in which our results are compared with the results obtained by the Lyapunov and Bogdanov methods by estimating the norms of solutions via Lozinskii logarithmic norms, and by the freezing method.     

四阶奇异边值问题的正解

本文利用上下解方法和极大值原理给出了四阶微分方程的奇异边值问题有C2[0,1]和C3[0,1]正解存在的充分必要条件.     

A generalization of Vinograd's theorem for dynamical systems

The theory of dynamical systems has been expanded by the introduction of local dynamical systems [10, 4, 9] and local semidynamical systems [1]. Using integral curves of autonomous ordinary differential equations to illustrate these generalizations, we find that, roughly, the integral curves form a local dynamical system if solutions exist and are unique without requiring existence for all time, and the integral curves form a local semidynamical system if solutions exist and are unique in the positive sense but need not exist for all positive time. In addition to autonomous ordinary differential equations, the enlarged theory of dynamical systems has applications to nonautonomous ordinary differential equations, certain partial differential equations, functional differential equations, and Volterra Integral equations [9, 1, 2, 8], respectively. All of these have metric phase spaces. Since many dynamic considerations are invariant to reparameterizations, it is of interest to known when a local dynamical (or semidynamical) system can be reparameterized to yield a “global” dynamical (or semidynamical) system. For autonomous ordinary differential equations, Vinograd [7] has shown that the local dynamical system on an open subset ofRⁿ formed by integral curves is isomorphic (in the sense of Nemytskii and Stepanov) to a global dynamical system. In an extensive study of isomorphisms, Ura [12] has expanded the Gottschalk-Hedlund notion of an isomorphism and restated Vinograd's result in terms of a reparameterization. In this paper we study the problem of finding a global dynamical (or semidynamical) system which is isomorphic to a given local system. A necessary and sufficient condition is found which is then used to show that the Vinograd result holds on metric spaces.     

An algorithmic method for showing existence of nontrivial non-classical symmetries of partial differential equations without solving determining equations

In this paper, based on differential characteristic set theory and the associated algorithm (also called Wu?s method), an algorithmic method is presented to decide on the existence of a nontrivial non-classical symmetry of a given partial differential equation without solving the corresponding nonlinear determining system. The theory and algorithm give a partial answer for the open problem posed by P.A. Clarkson and E.L. Mansfield in [21] on non-classical symmetries of partial differential equations. As applications of our algorithm, non-classical symmetries and corresponding invariant solutions are found for several evolution equations.