A Nine-modes Truncation of the Plane Incompressible Navier-Stokes Equations

In this paper a nine-modes truncation of Navier-Stokes equations for a two-dimensional incompressible fluid on a torus is obtained. The stationary solutions, the existence of attractor and the global stability of the equations are firmly proved. What is more, that the force f acts on the mode ks and k7 respectively produces two systems, which lead to a much richer and varied phenomenon. Numerical simulation is given at last, which shows a stochastic behavior approached through an involved sequence of bifurcations.     

Some problems on the global attractivity of linear nonautonomous difference equations

This paper is to solve several problems on the global attractivity of the zero solution of the nonautonomous difference equation xn+1 - xn + Pnxn-kn = 0,n ∈ Z(0), where {Pn} is a sequence of nonnegative real numbers, and {kn} is a sequence of nonnegative integers with n - kn→∞ as n→∞.     

平面不可压缩的Navier-Stokes方程的一个新七模截断(英文)

A new seven-modes truncation of Fourier series of Navier-Stokes equations for a two-dimensional incompressible fluid on a torus is obtained.And its stationary solutions,the existence of attractor and the global stability of the equations are firmly proved.At the same time,several issues such as some basic dynamical behaviors and routs to chaos are shown numerically by changing Reynolds number.The system exhibits a stochastic behavior approached through an involved sequence of bifurcations.     

LOCAL AND GLOBAL HOPF BIFURCATIONS IN A DELAYED HUMAN RESPIRATORY SYSTEM

This paper considers a delayed human respiratory model. Firstly, the stability of the equilibrium of the model is investigated and the occurrence of a sequence of Hopf bifurcations of the model is proved. Secondly, the explicit algorithms which determine the direction of the Hopf bifurcations and the stability of the bifurcating periodic solutions are derived by applying the normal form method and the center manifold theory. Finally, the existence of the global periodic solutions is showed under some assumptions on the model.     

AN INTERVAL ALGORITHM FOR CONSTRAINED GLOBAL OPTIMIZATION

In order to solve the constrained global optimization problem,we use penalty functions not only on constraints but also on objective function. Then within the framework of interval analysis,an interval Branch-and-Bound algorithm is given,which does not need to solve a sequence of unconstrained problems. Global convergence is proved. Numerical examples show that this algorithm is efficient.     

CHARACTERIZATION FOR BINOMIAL SEQUENCES AMONG RENEWAL SEQUENCES

In this paper a binomial sequence is defined as a special sequence whose renewal lifes are identically distributed with a common geometric distribution. Therefore, it can be regarded as the discrete version of a Poisson process. Mainly, we discuss the characterization problem associated with binomial sequences. First, we sketch the properties of some important quantities of a renewal sequence. The emphasis of discussion is laid on the current life, the residual life and the total life. Then, we describe three main approaches to identify a geometric distribution. Finally, based on these concepts and techniques, we give a series of characterization theorems for a binomial sequence. These results are quite similar to those obtained for a Poisson process.     

A GLOBALLY CONVERGENT ALGORITHM FOR THE EUCLIDEAN MULTIPLICITY LOCATION PROBLEM

The Euclidean single facility location problem (ESFL) and the Euclidean multiplicity lo-cation problem (EMFL) are two special nonsmooth convex programming problems which haveattracted a largr literature. For the ESFL problem. there are algorithms which converge bothglobally and quadratically For the EMFL problem, there are some quadratically convergentalgorithms. but for global convergencel they all need nontrivial assumptions on the problem.In this paper, we present an algorithm for EMFL. With no assumption on the problem, it isproved that from any initial point, this algorithm generates a sequence of points which convergesto the closed convex set of optimal solutions of EMFL.     

A STONE-WEIERSTRASS THEOREM FOR CERTAIN DISCONTINUOUS FUNCTIONS

La Abe point separating uiatal subalgebra. of C(T) where T is a compact metric space. For each bounded function f:T which is continuous on the complement of a meagre subset of T there exists a sequence (wn) of elements of the algebra A such that the sequence (w) converges uniformly to the function f on each compact subset of the interior of the continuity points of the function f.     

A MODIFIED LEVENBERG-MARQUARDT ALGORITHM FOR SINGULAR SYSTEM OF NONLINEAR EQUATIONS

Based on the work of paper,we propose a modified Levenberg-Marquardt algoithm for solving singular system of nonlinear equations F(x)=0,where F(x):R^n→R^n is continuously differentiable and F‘(x)is Lipschitz continuous.The algorithm is equivalent to a trust region algorithm in some sense,and the global convergence result is given.The sequence generated by the algorithm converges to the solution quadratically,if ||F(x)||2 provides a local error bound for the system of nonlinear equations.Numerical results show that the algorithm performs well.     

GLOBAL ATTRACTIVITY OF A DIFFERENCE EQUATION

In this paper,we investigate the global stability of all positive solutions to a difference equation.We show that the unique positive equilibrium of the equation is a global attractor with a basin under some certain conditions on the coefficient.     

A representation of cyclically compact operators on Kaplansky–Hilbert modules

We give a representation of cyclically compact self-adjoint operators on Kaplansky–Hilbert modules and characterize the global eigenvalues of such operators by a sequence consisting of their global eigenvalues taken in the corresponding representation.     

反应扩散方程的渐近吸引子

本文考虑了反应扩散方程的渐近吸引子，即构造了一个有限维解序列。首先利用数学归纳法证明了该解序列不会远离方程的整体吸引子，其次证明了它在长时间后无限趋于方程的整体吸引子，并且给出了渐近吸引子的维数估计。     

Unified theory of augmented Lagrangian methods for constrained global optimization

We classify in this paper different augmented Lagrangian functions into three unified classes. Based on two unified formulations, we construct, respectively, two convergent augmented Lagrangian methods that do not require the global solvability of the Lagrangian relaxation and whose global convergence properties do not require the boundedness of the multiplier sequence and any constraint qualification. In particular, when the sequence of iteration points does not converge, we give a sufficient and necessary condition for the convergence of the objective value of the iteration points. We further derive two multiplier algorithms which require the same convergence condition and possess the same properties as the proposed convergent augmented Lagrangian methods. The existence of a global saddle point is crucial to guarantee the success of a dual search. We generalize in the second half of this paper the existence theorems for a global saddle point in the literature under the framework of the unified classes of augmented Lagrangian functions.     

An algorithm for global optimization of Lipschitz continuous functions

An algorithm is presented which locates the global minimum or maximum of a function satisfying a Lipschitz condition. The algorithm uses lower bound functions defined on a partitioned domain to generate a sequence of lower bounds for the global minimum. Convergence is proved, and some numerical results are presented.     

Convergence of the Simulated Annealing Algorithm for Continuous Global Optimization

A class of simulated annealing algorithms for continuous global optimization is considered in this paper. The global convergence property is analyzed with respect to the objective value sequence and the minimum objective value sequence induced by simulated annealing algorithms. The convergence analysis provides the appropriate conditions on both the generation probability density function and the temperature updating function. Different forms of temperature updating functions are obtained with respect to different kinds of generation probability density functions, leading to different types of simulated annealing algorithms which all guarantee the convergence to the global optimum.     

On partial sums of a gaussian sequence with stationary increments

We establish large increment properties for a Gaussian sequence with stationary increments under global conditions. Limit theorems for partial sums of the sequence with nonpositive correlation functions or the correlation functions on their speed of convergence to zero are proved via estimating a probability inequality on the supremum of Gaussian processes     

New Reflection Generator for Simulated Annealing in Mixed-Integer/Continuous Global Optimization

To reduce the well-known jamming problem in global optimization algorithms, we propose a new generator for the simulated annealing algorithm based on the idea of reflection. Furthermore, we give conditions under which the sequence of points generated by this simulated annealing algorithm converges in probability to the global optimum for mixed-integer/continuous global optimization problems. Finally, we present numerical results on some artificial test problems as well as on a composite structural design problem.     

On the convergence of higher-order orthogonal iteration

The higher-order orthogonal iteration (HOOI) has been popularly used for finding a best low-multilinear rank approximation of a tensor. However, its convergence is still an open question. In this paper, we first analyse a greedy HOOI, which updates each factor matrix by selecting from the best candidates one that is closest to the current iterate. Assuming the existence of a block-nondegenerate cluster point, we establish its global iterate sequence convergence through the so-called Kurdyka–?ojasiewicz property. In addition, we show that if the starting point is sufficiently close to any block-nondegenerate globally optimal solution, the greedy HOOI produces an iterate sequence convergent to a globally optimal solution. Relating the iterate sequence by the original HOOI to that by the greedy HOOI, we then show that the original HOOI has global convergence on the multilinear subspace sequence and thus positively address the open question.     

A convex analysis approach for convex multiplicative programming

Global optimization problems involving the minimization of a product of convex functions on a convex set are addressed in this paper. Elements of convex analysis are used to obtain a suitable representation of the convex multiplicative problem in the outcome space, where its global solution is reduced to the solution of a sequence of quasiconcave minimizations on polytopes. Computational experiments illustrate the performance of the global optimization algorithm proposed.      

Finite dimensional approximation to solutions of minimization problems in functional spaces

In this paper we consider minimization problems whose objectives are defined on functional spaces. The integral global optimization technique is applied to characterize a global minimum as the limit of a sequence of approximating solutions on finite dimensional subspaces. Necessary and sufficient optimality conditions are presented. A variable measure algorithm is proposed to find such approximating solutions. Examples are presented to illustrate the variable measure method