非扩张映象有限族的公共不动点的隐式迭代方法

本文在实一致凸和q一致光滑Banach空间中研究了一类新的有限族非扩张映象的公共不动点的具误差和具扰动映射的隐式迭代程序并且得到了一些收敛性定理.特别地,获得了该隐式迭代程序强收敛性的充要条件.本文所得结论推广了文[1,2]中的相应结果.     

具随机性误差隐迭代程序的收敛性

在任意Banauch空间中,证明了有限族渐近半压缩映象具随机性误差的隐迭代程序逼近其公共不动点的强收敛性定理.所得结论推广和改进了引文中的相应结果.     

关于Ф-伪压缩型映象的具误差的Ishikawa和Mann迭代过程的收敛性问题

在Bannah空间中,研究了多值Ф-伪压缩型映象的具误差的Ishikawa和Mann迭代过程的收敛性问题.所得结果改进,发展和统一了许多人的最新结果.     

Φ-伪压缩型映象的具误差的Ishikawa和Mann迭代程序的收敛性问题

引入Φ＿ 伪压缩型映象的概念，并研究了此类映象的具误差的Ｉｓｈｉｋａｗａ 和Ｍａｎｎ 迭代程序的收敛性问题·　本文结果改进和发展了许多人的最新结果·     

渐近非扩张映象具误差的迭代序列的收敛性

在Banach空间中引入渐近非扩张映象和非扩张映象某些类型的具误差的迭代序列,并研究了这些迭代序列的收敛性问题.本文的结果改进、推广和完善了最新的一些结果.     

凸度量空间中广义拟压缩映射具误差的Ishikawa型迭代序列的收敛性

构造了具误差的Ishikawa和Mann型迭代序列,研究了凸度量空间中广义拟压缩映射的收敛性问题.所的结果改进和推广了Ciric、Rhoades、LiuQH、XuHK、田有先和张石生等人的相应结果.     

具误差的三种迭代收敛的等价性

考虑了具误差的Mann迭代,Ishikawa迭代和三重迭代对中间意义下的渐进非扩张映射和强逐次伪压缩映射收敛的等价性.我们的主要结果改善和推广了近期该方向研究所得到的某些成果.     

关于增生算子方程的具误差的Ishikawa迭代序列的收敛率估计

设X是一实的Banach空间,TLX→X是—Lipschitz的增生算子;证明了具误差的Ishikawa迭代序列强收敛到x＋Tx=f的唯一解;得到一个一般的收敛率估计式．进一步得到：若了T：X→X是—Lipschitz的强增生算子,则具误差的Ishikawa迭代序列强收敛到Tx=f的唯一解．文中结果推广和发展了已有的相关结果．     

Banach空间中强增生型变分包含解的具误差的Ishikawa迭代逼近

该文研究Ｂａｎａｃｈ空间中一类强增生型变分包含解的存在性及其具误差的Ｉｓｈｉｋａｗａ迭代程序的收敛性问题．该文结果是几位作者早期与最近的相应结果的改进和推广．     

非线性算子具误差的隐迭代程序的强收敛性

设K是一致凸Banach空间中的非空闭凸子集,T_i:K→K(i=1,2,…,N)是有限族完全渐近非扩张映象.对任意的x_0∈K,具误差的隐迭代序列{x_n}为:x_n=α_nx_n-1+β_nT_n~kx_n+γ_nu_n,n≥1,其中{α_n},{β_n},{γ_n}■[0,1]满足α_n+β_n+γ_n=1,{u_n}是K中的有界序列.在一定的条件下,该文建立了隐迭代序列{x_n}的强收敛性.得到隐迭代序列{x_n}强收敛于有限族完全渐近非扩张映象公共不动点的充要条件.所得结果改进和推广了Shahzad与Zegeye,Zhou与Chang,Chang,Tan,Lee与Chan等人的相应结果.     

Explicit iteration schemes for minimization problems arising from image denoising

The purpose of this paper is to investigate explicit iteration schemes for minimization problems arising from image denoising. In particular, we propose explicit iteration schemes based on matrix splitting. When the matrix splitting is done by the symmetric Gauss–Seidel method, we establish convergence of the scheme with no restriction on the step size of the iteration. If the matrix splitting is done by the Gauss–Seidel method, we show that the iteration scheme still converges, provided the step size of each iteration is sufficiently small.     

关于Banach空间非扩张半群的强收敛定理

在Banach空间框架下,建立了几个关于非扩张半群显式迭代序列的强收敛定理.所得结果不仅推广和改进了Shioji-Takahashi,Suzuki,Xu以及Aleyner-Reich等人的相应结果,而且还部分肯定地回答了Suzuki和Xu提出的两个公开问题.     

Implicit iteration scheme with perturbed mapping for common fixed points of a finite family of nonexpansive mappings

In this paper we propose a new implicit iteration scheme with perturbed mapping for approximation of common fixed points of a finite family of nonexpansive mappings. We establish some convergence theorems for this implicit iteration scheme. In particular, necessary and sufficient conditions for strong convergence of this implicit iteration scheme were obtained.     

Relaxed Cutting Plane Method for Solving Linear Semi-Infinite Programming Problems

One of the major computational tasks of using the traditional cutting plane approach to solve linear semi-infinite programming problems lies in finding a global optimizer of a nonlinear and nonconvex program. This paper generalizes the Gustafson and Kortanek scheme to relax this requirement. In each iteration, the proposed method chooses a point at which the infinite constraints are violated to a degree, rather than a point at which the violations are maximized. A convergence proof of the proposed scheme is provided. Some computational results are included. An explicit algorithm which allows the unnecessary constraints to be dropped in each iteration is also introduced to reduce the size of computed programs.     

Convergence theorems for nonexpansive mappings and feasibility problems

In this paper, we introduce an iteration scheme given by finite nonexpansive mappings in Banach spaces and then prove weak convergence theorems which are connected with the problem of image recovery. Using the results, we consider the problem of finding a common fixed point of finite nonexpansive mappings.     

一致凸Banach空间中渐近非扩展映象的迭代格式之新强收敛定理

通过使用新的分析技巧，建立了(关于)渐近非扩展映象的修正的迭代格式的强收敛定理．所得结果改进了Schu，Rhoades以及其他作相关的结果。     

Dual Convergences of Iteration Processes for Nonexpansive Mappings in Banach Spaces

In this paper we establish a dual weak convergence theorem for the Ishikawa iteration process for nonexpansive mappings in a reflexive and strictly convex Banach space with a uniformly Gâteaux differentiable norm, and then apply this result to study the problem of the weak convergence of the iteration process.     

关于有限族Lipschitz映射多步Ishikawa迭代算法的收敛性及其应用

本文的目的是研究Lipschitz映射公共不动点问题.基于传统的Ishikawa迭代和Noor迭代方法,我们引入多步Ishikawa迭代算法,并且分别给出了该算法强收敛于有限族拟-Lipschitz映射和伪压缩映射公共不动点的充分必要条件.此外,我们证明了该算法强收敛到非扩张映射的公共不动点.作为应用,我们给出数值试验证实所得的结论.     

广义复合隐迭代格式逼近非扩张映像公共不动点

提出并使用如下广义复合隐迭代格式逼近非扩张映像族{Ti}Ni=1公共不动点:{xn=αnxn-1 (1-αn)Tnyn,yn=rnxn snxn-1 tnTnxn wnTnxn-1,rn sn tn wn=1,{αn},{rn},{sn},{tn},{wn}∈[0,1],这里Tn=TnmodN.该文提出的广义复合隐迭代格式包含了目前多种迭代格式,因此,所得强弱收敛定理推广及发展了Mann,Ishikawa,XuandOri,等许多作者的结果.