基于演化博弈视角的政府预算博弈模型设计及分析

针对政府预算体系,由于部门采取的行为策略是基于有限理性而做出的,所以博弈双方的策略选择实际上是不断调整的,并且是根据对方策略的变化而不断变化的。因此,运用演化博弈工具来研究政政府预算体系更符合现实情况。基于此,从演化博弈理论的研究视角探讨了预算审批部门、预算申报部门和财政支出部门决策的演化过程,建立了预算审批部门和预算申报部门以及财政支出部门之间的演化博弈模型。分析了审批部门、申报部门和支出部门的行为特征,根据复制者动态方程得到了参与者的行为演化规律和行为演化稳定策略。最后,文章通过数值算例对结论进行了论证。     

MNTZ RATIONAL APPROXIMATION FOR SPECIAL FUNCTION CLASSES IN Ba[0,1] SPACES

In this paper,we research the Mntz rational approximation of two kinds of special function classes,and give the corresponding estimates of approximation rates of these classes.     

三维周期结构弱无条件稳定时域有限差分算法

从麦克斯韦方程出发,导出了适用于周期结构的三维弱无条件稳定时域有限差分（FDTD）算法的迭代式,在理论上证明了其稳定性条件,其稳定性条件比普通FDTD的稳定性条件要宽松,并将周期边界条件应用到迭代式中,得到了可直接编程迭代的方程,给出了对其特有的一类非三对角阵的解决办法。最后通过算例将计算结果与常规FDTD及ADI-FDTD计算结果比较,验证了算法的精确性和有效性。     

Weak mixing implies mixing for maps on topological graphs

In section 1, we correct an error in the proof of Lemma 3.1 in L. Alsedà, M.A. del Río, and J.A. Rodríguez. Transitivity and dense periodicity for graph maps. J. Difference Equ. Appl. 9, 577–598, 2003. In section 2 we give a simple proof that weak mixing implies mixing for maps on topological graphs. The proofs can also be extended to (not necessarily compact) intervals, so in particular, this paper shows that for one-dimensional manifolds, weak mixing implies mixing.     

Ergodic properties of operators in some semi-Hilbertian spaces

This article deals with linear operators T on a complex Hilbert space ?, which are bounded with respect to the seminorm induced by a positive operator A on ?. The A-adjoint and A ^1/2-adjoint of T are considered to obtain some ergodic conditions for T with respect to A. These operators are also employed to investigate the class of orthogonally mean ergodic operators as well as that of A-power bounded operators. Some classes of orthogonally mean ergodic or A-ergodic operators, which come from the theory of generalized Toeplitz operators are considered. In particular, we give an example of an A-ergodic operator (with an injective A) which is not Cesàro ergodic, such that T ^?* is not a quasiaffine transform of an orthogonally mean ergodic operator.     

Approximation and optimization of discrete and differential inclusions described by inequality constraints

In the first part of this article optimization of polyhedral discrete and differential inclusions is considered, the problem is reduced to convex minimization problem and the necessary and sufficient condition for optimality is derived. The optimality conditions for polyhedral differential inclusions based on discrete-approximation problem according to continuous problems are formulated. In particular, boundedness of the set of adjoint discrete solutions and upper semi-continuity of the locally adjoint mapping are proved. In the second part of this article an optimization problem described by convex inequality constraint is studied. By using the equivalence theorem concerning the subdifferential calculus and approximating method necessary and sufficient condition for discrete-approximation problem with inequality constraint is established.     

Generalized weak sharp minima in cone-constrained convex optimization on Hadamard manifolds

In this paper, a convex optimization problem with cone constraint (for short, CPC) is introduced and studied on Hadamard manifolds. Some criteria and characterizations for the solution set to be a set of generalized global weak sharp minima, generalized local weak sharp minima and generalized bounded weak sharp minima for (CPC) are derived on Hadamard manifolds.     

A relaxed self-adaptive CQ algorithm for the multiple-sets split feasibility problem

The multiple-sets split feasibility problem (MSFP) is to find a point belongs to the intersection of a family of closed convex sets in one space, such that its image under a linear transformation belongs to the intersection of another family of closed convex sets in the image space. Many iterative methods can be employed to solve the MSFP. Jinling Zhao et al. proposed a modification for the CQ algorithm and a relaxation scheme for this modification to solve the MSFP. The strong convergence of these algorithms are guaranteed in finite-dimensional Hilbert spaces. Recently López et al. proposed a relaxed CQ algorithm for solving split feasibility problem, this algorithm can be implemented easily since it computes projections onto half-spaces and has no need to know a priori the norm of the bounded linear operator. However, this algorithm has only weak convergence in the setting of infinite-dimensional Hilbert spaces. In this paper, we introduce a new relaxed self-adaptive CQ algorithm for solving the MSFP where closed convex sets are level sets of some convex functions such that the strong convergence is guaranteed in the framework of infinite-dimensional Hilbert spaces. Our result extends and improves the corresponding results.