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1.
Г-环的单位元   总被引:1,自引:1,他引:0       下载免费PDF全文
Γ-环的乘法单位元比结合环的乘法单位元更复杂,更富有变化.首先它有单位元,α-单位元(强单位元)之分,其次它具有与结合环单位元相异的性质,对此本文逐一阐述.此外还探讨了Γ-环M与其矩阵环Mm,n单位元间的关系.在导入Γ-环的特征这一概念后,证明了具有单位元Γ-环的特征的一些性质.  相似文献   

2.
本文定义了次弱ГN-环,证明了若次弱ГN一环M的强诣零根N是有限生成的,则M/N一定是强诣零半单的.并且.如果M存在强幂零根I,则N=I.  相似文献   

3.
王顶国 《数学学报》1997,40(2):221-226
设M是Nobusawa意义下的Г-环,S.Kyuno定义了环M_2=其中R,L分别是M的右、左算子环.本文首先刻画了环M_2的本原理想与Ja-cobson根.其次引进了一类新的Г-环称为PM Г-环,建立了Г-环M、矩阵Г_(n,m)-环M_(m,n)、Г-环M的右(左)算子环R(L)、M-环Г及M_2的PM性质之间的关系.最后,给出了Г-环一般形式的Jacobson性质,Jacobson性质、Brown-McCoy性质以及PM性质为其特殊情况.  相似文献   

4.
设M是Nobusawa意义下的Г-环,S.Kyuno定义了环M_2=其中R,L分别是M的右、左算子环.本文首先刻画了环M_2的本原理想与Ja-cobson根.其次引进了一类新的Г-环称为PM Г-环,建立了Г-环M、矩阵Г_(n,m)-环M_(m,n)、Г-环M的右(左)算子环R(L)、M-环Г及M_2的PM性质之间的关系.最后,给出了Г-环一般形式的Jacobson性质,Jacobson性质、Brown-McCoy性质以及PM性质为其特殊情况.  相似文献   

5.
王志玺 《中国科学A辑》1993,36(10):1043-1046
设 A 是左、右 Noether 环,x 是 A 的中心正则元.Ax 表示 A 关于乘闭子集{1,x,x2,…}的局部化.M 是 A-模且 x 是 M 的非零因子.本文确定了入射维数IdA(M),IdAx(Mx)与 IdA/xA(M/xM)三者之间的等式关系,并把结果应用于滤环(filtered ring)的 Rees 环,得到了 Ekstr(?)m 的两个结果的统一形式和改进,同时推广了 Li Huishi,M.Van den Bergh 和 F.Van Oystaeyen 的相应结果.  相似文献   

6.
FP-内射模决定凝聚环与IF环   总被引:5,自引:2,他引:3  
我们在§2.中证明了 1.可换环是Noether环?平坦模与内射模的张量积是内射模。本文的其余部分考虑用FP-内射性质来刻划凝聚环、CF环及IF环,主要结果有: 2.对于环R,下述各条等价: (1) R是左凝聚环。 (2) 对于任意有限表示模RM,FR-内射模RN,都有ExtR2(M,N)=0 (3) 若N1?RN都是FP-内射的,则N/N1是FP-内射  相似文献   

7.
无单位元的群分次环、Smash积及其一个应用   总被引:1,自引:0,他引:1  
本文对于具有局部单位元的群分次环R证明了左R#C*-模范畴与分次左R-模范畴是同构的,并给出R是分次右完全环的一些充要条件.  相似文献   

8.
FP—内射环和IF环的几个特征   总被引:3,自引:1,他引:2  
本文给出了FP—内射环和IF环的如下几个特征:(l)R为右FP—内射环当且仅当任意左R—模正合列Kn→Kn→N→0 N为无挠模,当且仅当任一n阶矩阵环为右P—内射环;(2)R为左IF环当且仅当任一有限生成左R—模均可嵌入平坦模;(3)R为IF环当且仅当R为伪凝聚的上平坦环。  相似文献   

9.
给出了环T=(R M N S)(θ,ψ) 整体维数的一个估计:若T为左Noether环,且M为平坦右S模,则max{LGD(R),LGD(S)}≤LGD(T)≤1+max{LGD(S),1+PD(sN)+LGD(R/MN)}.  相似文献   

10.
蒋滋梅 《中国科学A辑》1996,39(4):317-321
令R是含非零基座的本原环,M是R的忠实既约右模,△是M的中心化子,L=∑ L1是R的可列无限多个极小右理想的直和.那末R中存在一族子集 Iα={ea1}i=1,(α∈W,|W|无限).对任意α∈W,Iα是R的可列无限多个秩为1的正交幂等元集且使举例说明存在本原环R及其可列无限多个极小右理想Li(i=1,…)的直和L=∑ L1,而R中不存在可列无限多个秩为1的正交幂等元集{εi}i=1…使得既满足L=∑ε1R,且{εi}i=1…又可以扩展为M的一个基的对应基.  相似文献   

11.
对于非线性约束的优化问题.最近给出的各种SQP算法均采用罚函数技巧以保证算法的全局收敛性,因而都必须小心地调整惩罚参数。本文给出一个不依赖于惩罚参数、每步迭代的校正矩阵也不需正定且仍具有全局收敛性的SQP方法,而且罚函数形式简单、具有和约束函数同阶的光滑性.  相似文献   

12.
In this paper, we consider two algorithms for nonlinear equality and inequality constrained optimization. Both algorithms utilize stepsize strategies based on differentiable penalty functions and quadratic programming subproblems. The essential difference between the algorithms is in the stepsize strategies used. The objective function in the quadratic subproblem includes a linear term that is dependent on the penalty functions. The quadratic objective function utilizes an approximate Hessian of the Lagrangian augmented by the penalty functions. In this approximation, it is possible to ignore the second-derivative terms arising from the constraints in the penalty functions.The penalty parameter is determined using a strategy, slightly different for each algorithm, that ensures boundedness as well as a descent property. In particular, the boundedness follows as the strategy is always satisfied for finite values of the parameter.These properties are utilized to establish global convergence and the condition under which unit stepsizes are achieved. There is also a compatibility between the quadratic objective function and the stepsize strategy to ensure the consistency of the properties for unit steps and subsequent convergence rates.This research was funded by SERC and ESRC research contracts. The author is grateful to Professors Laurence Dixon and David Mayne for their comments. The numerical results in the paper were obtained using a program written by Mr. Robin Becker.  相似文献   

13.
a special penalty method is presented to improve the accuracy of the standard penaltymethod (or solving Stokes equation with nonconforming finite element, It is shown that thismethod with a larger penalty parameter can achieve the same accuracy as the staodaxd methodwith a smaller penalty parameter. The convergence rate of the standard method is just hall order of this penalty method when using the same penalty parameter, while the extrapolationmethod proposed by Faik et al can not yield so high accuracy of convergence. At last, we alsoget the super-convergence estimates for total flux.  相似文献   

14.
The alternating direction method of multipliers (ADMM) is a benchmark for solving a two-block linearly constrained convex minimization model whose objective function is the sum of two functions without coupled variables. Meanwhile, it is known that the convergence is not guaranteed if the ADMM is directly extended to a multiple-block convex minimization model whose objective function has more than two functions. Recently, some authors have actively studied the strong convexity condition on the objective function to sufficiently ensure the convergence of the direct extension of ADMM or the resulting convergence when the original scheme is appropriately twisted. We focus on the three-block case of such a model whose objective function is the sum of three functions, and discuss the convergence of the direct extension of ADMM. We show that when one function in the objective is strongly convex, the penalty parameter and the operators in the linear equality constraint are appropriately restricted, it is sufficient to guarantee the convergence of the direct extension of ADMM. We further estimate the worst-case convergence rate measured by the iteration complexity in both the ergodic and nonergodic senses, and derive the globally linear convergence in asymptotical sense under some additional conditions.  相似文献   

15.
In this paper, we propose a new penalty-free-type method for nonlinear equality constrained problems. The new algorithm uses trust region framework and feasibility safeguarding technique. Moreover, it has no choice of penalty parameter and penalty function as a merit function, and it does not use the filter technique to avoid the penalty function either. We analyze the global convergence of the main algorithm under the standard assumptions. The preliminary numerical tests are reported.  相似文献   

16.
We present an interior-point penalty method for nonlinear programming (NLP), where the merit function consists of a piecewise linear penalty function and an ? 2-penalty function. The piecewise linear penalty function is defined by a set of break points that correspond to pairs of values of the barrier function and the infeasibility measure at a subset of previous iterates and this set is updated at every iteration. The ? 2-penalty function is a traditional penalty function defined by a single penalty parameter. At every iteration the step direction is computed from a regularized Newton system of the first-order equations of the barrier problem proposed in Chen and Goldfarb (Math Program 108:1?C36, 2006). Iterates are updated using a line search. In particular, a trial point is accepted if it provides a sufficient reduction in either of the penalty functions. We show that the proposed method has the same strong global convergence properties as those established in Chen and Goldfarb (Math Program 108:1?C36, 2006). Moreover, our method enjoys fast local convergence. Specifically, for each fixed small barrier parameter???, iterates in a small neighborhood (roughly within o(??)) of the minimizer of the barrier problem converge Q-quadratically to the minimizer. The overall convergence rate of the iterates to the solution of the nonlinear program is Q-superlinear.  相似文献   

17.
We propose a differential evolution-based algorithm for constrained global optimization. Although differential evolution has been used as the underlying global solver, central to our approach is the penalty function that we introduce. The adaptive nature of the penalty function makes the results of the algorithm mostly insensitive to low values of the penalty parameter. We have also demonstrated both empirically and theoretically that the high value of the penalty parameter is detrimental to convergence, specially for functions with multiple local minimizers. Hence, the penalty function can dispense with the penalty parameter. We have extensively tested our penalty function-based DE algorithm on a set of 24 benchmark test problems. Results obtained are compared with those of some recent algorithms.  相似文献   

18.
本文给出了广义可微精确罚函数的概念及一类所谓广义限域可微精确罚函数.本文预先选定罚因子,将不等式约束问题化为单一的无约束问题,并给出了具全局收敛性的算法.本文的罚函数构造简单,假设条件少而且算法的构造与收敛性结果是独特的.  相似文献   

19.
This paper is concerned with the convergence analysis of power penalty method to pricing American options on discount bond, where the single factor Cox–Ingrosll–Ross model is adopted for the short interest rate. The valuation of American bond option is usually formulated as a partial differential complementarity problem. We first develop a power penalty method to solve this partial differential complementarity problem, which produces a nonlinear degenerated parabolic PDE. Within the framework of variational inequalities, the solvability and convergence properties of this penalty approach are explored in a proper infinite dimensional space. Moreover, a sharp rate of convergence of the power penalty method is obtained. Finally, we show that the power penalty approach is monotonically convergent with the penalty parameter.  相似文献   

20.
The EM algorithm is a widely used methodology for penalized likelihood estimation. Provable monotonicity and convergence are the hallmarks of the EM algorithm and these properties are well established for smooth likelihood and smooth penalty functions. However, many relaxed versions of variable selection penalties are not smooth. In this paper, we introduce a new class of space alternating penalized Kullback proximal extensions of the EM algorithm for nonsmooth likelihood inference. We show that the cluster points of the new method are stationary points even when they lie on the boundary of the parameter set. We illustrate the new class of algorithms for the problems of model selection for finite mixtures of regression and of sparse image reconstruction.  相似文献   

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