Bi-extrapolated subgradient projection algorithm for solving multiple-sets split feasibility problem

This paper deals with a bi-extrapolated subgradient projection algorithm by intro- ducing two extrapolated factors in the iterative step to solve the multiple-sets split feasibility problem. The strategy is intend to improve the convergence. And its convergence is proved un- der some suitable conditions. Numerical results illustrate that the bi-extrapolated subgradient projection algorithm converges more quickly than the existing algorithms.

New hybrid inertial CQ projection algorithms with line-search process for the split feasibility problem

In this paper, we propose two hybrid inertial CQ projection algorithms with linesearch process for the split feasibility problem. Based on the hybrid CQ projection algorithm, we firstly add the inertial term into the iteration to accelerate the convergence of the algorithm, and adopt flexible rules for selecting the stepsize and the shrinking projection region, which makes an optimal stepsize available at each iteration. The shrinking projection region is the intersection of three sets, which are the set C and two hyperplanes. Furthermore, we modify the Armijo-type line-search step in the presented algorithm to get a new algorithm.The algorithms are shown to be convergent under certain mild assumptions. Besides, numerical examples are given to show that the proposed algorithms have better performance than the general CQ algorithm.

FURTHER INVESTIGATION INTO APPROXIMATION OF A COMMON SOLUTION OF FIXED POINT PROBLEMS AND SPLIT FEASIBILITY PROBLEMS

The purpose of this paper is to study and analyze an iterative method for finding a common element of the solution set ~ of the split feasibility problem and the set F（T） of fixed points of a right Bregman strongly nonexpansive mapping T in the setting of p- uniformly convex Banach spaces which are also uniformly smooth. By combining Mann＇s iterative method and the Halpern＇s approximation method, we propose an iterative algorithm for finding an element of the set F（T）∩Ω moreover, we derive the strong convergence of the proposed algorithm under appropriate conditions and give numerical results to verify the efficiency and implementation of our method. Our results extend and complement many known related results in the literature.

GENERAL SPLIT FEASIBILITY PROBLEMS FOR TWO FAMILIES OF NONEXPANSIVE MAPPINGS IN HILBERT SPACES

The purpose of this article is to introduce a general split feasibility problems for two families of nonexpansive mappings in Hilbert spaces. We prove that the sequence generated by the proposed new algorithm converges strongly to a solution of the general split feasibility problem. Our results extend and improve some recent known results.

求解分裂可行问题的次梯度投影松弛算法

在无限维Hilbert空间中,区别于现有许多算法中的正交投影,采用次梯度投影法,提出求解分裂可行问题的次梯度投影松弛算法,并利用次梯度算子的cutter性质以及分类讨论的思想,证明了次梯度投影松弛算法生成的序列弱收敛于分裂可行问题的解.

混合Bregman投影算法在Banach空间中分裂不动点问题的强收敛性

在p-一致凸且一致光滑的Banach空间中,利用Bregman投影,构造一新的混合投影迭代算法,逼近Bregman拟严格伪压缩映射不动点集和分裂可行性问题的公共解.目的是将2017年Chen J Z,Hu H Y和Ceng L C的研究结果中的迭代系数α_(n)须满足0<c≤a_(n)≤d<1证明对α_(n)≡1或α_(n)≡0时亦成立.所得的结果是对2017年Chen J Z,Hu H Y和Ceng L C相应结果的拓展和补充.

A New Inertial Self-adaptive Gradient Algorithm for the Split Feasibility Problem and an Application to the Sparse Recovery Problem

In this paper,by combining the inertial technique and the gradient descent method with Polyak's stepsizes,we propose a novel inertial self-adaptive gradient algorithm to solve the split feasi-bility problem in Hilbert spaces and prove some strong and weak convergence theorems of our method under standard assumptions.We examine the performance of our method on the sparse recovery prob-lem beside an example in an infinite dimensional Hilbert space with synthetic data and give some numerical results to show the potential applicability of the proposed method and comparisons with related methods emphasize it further.

分裂可行性问题的外推加速线性交替方向乘子法及其全局收敛性

针对在图像重建以及语言处理系统等领域有着广泛应用的分裂可行性问题(SFP)的最优化求解,提出了外推加速线性交替方向乘子法。首先将SFP描述为一个具有线性约束的可分离凸极小化问题;然后引进外推线性交替方向乘子法,利用问题的可分离结构,产生了具有闭式解的子问题,并在适当条件下证明了该算法的全局收敛性;最后,通过数值实验验证了该算法的可行性和有效性。

张量分裂可行域问题的有效投影迭代法

投影法是解决多集分裂可行域问题的广泛且有效的研究方法.本文从分裂迭代视角出发,研究了求解张量可行域问题的高效投影分裂迭代方法.首先,利用投影算子将张量分裂可行域问题转化为多线性方程组.然后,借助加速超松弛法和对称(交替)加速超松弛法的高维化处理方式,推广到适合多线性方程组的求解框架.最后,通过对新的张量分裂迭代格式的谱半径的理论分析,证明了算法的收敛性.充分的数值测试验证了算法的有效性.

The Problem of Split Convex Feasibility and Its Alternating Approximation Algorithms

This paper studies the problem of split convex feasibility and a strong convergent alternating algorithm is established.According to this algorithm,some strong convergent theorems are obtained and an affirmative answer to the question raised by Moudafi is given.At the same time,this paper also generalizes the problem of split convex feasibility.

A Levenberg–Marquardt Method for Solving the Tensor Split Feasibility Problem

This paper considers the tensor split feasibility problem.Let C and Q be non-empty closed convex set and A be a semi-symmetric tensor.The tensor split feasibility problem is to find x∈C such that Axm−1∈Q.If we simply take this problem as a special case of the nonlinear split feasibility problem,then we can directly get a projection method to solve it.However,applying this kind of projection method to solve the tensor split feasibility problem is not so efficient.So we propose a Levenberg–Marquardt method to achieve higher efficiency.Theoretical analyses are conducted,and some preliminary numerical results show that the Levenberg–Marquardt method has advantage over the common projection method.

Hilbert空间中分裂可行性问题的改进Halpern迭代和黏性逼近算法

在无限维Hilbert空间中,提出了求解分裂可行性问题(SFP)的改进Halpern迭代和黏性逼近算法,证明了当参数满足一定条件时,由给定算法生成的序列强收敛到分裂可行性问题的一个解.这些结论推广了Deepho和Kumam近年来的一些结果.

Hilbert空间中求解分裂可行问题CQ算法的强收敛性

在Hilbert空间中,为了研究分裂可行问题迭代算法的强收敛性,提出了一种新的CQ算法.首先利用CQ算法构造了一个改进的Halpern迭代序列;然后通过把分裂可行问题转化为算子不动点,在较弱的条件下,证明了该序列强收敛到分裂可行问题的一个解.推广了Wang和Xu的有关结果.

分裂可行问题自适应步长惯性球松弛CQ算法

针对分裂可行性问题,在自适应步长球松弛CQ算法基础上引入惯性项,加快算法的收敛速度;同时,利用Halpern迭代格式调整算法,并证明算法在无限维Hilbert空间中强收敛。

分裂可行问题的两种强收敛CQ算法(英文)

为保证Hilbert空间中求解分裂可行问题迭代算法的强收敛性,本文首先通过引入三个参数序列提出了求解分裂可行问题的改进CQ算法,并在较弱的条件下证明了算法的强收敛性.然后改进算法中的一个算子,即选择另外一个参数序列嵌入到一个算子里,得到了一种新的算法.在参数序列满足一定条件下也证明了算法的强收敛性.本文拓展了现已有的相关研究成果.

强收敛的球松弛CQ算法及其应用

为了求解分裂可行问题,Yu等提出了一个球松弛CQ算法。由于该算法只需计算到闭球上的投影,同时不需要计算有界线性算子的范数,该算法是容易实现的。但是球松弛CQ算法在无穷维Hilbert空间中仅仅具有弱收敛性。首先构造了一个强收敛的球松弛CQ算法。在较弱的条件下,证明了算法的强收敛性。其次将该算法应用到一类闭凸集上的投影问题上。最后,数值试验验证了该算法的有效性。

分裂可行问题的一个强收敛算法

分裂可行问题是一类应用很广泛的最优化问题。经典的CQ算法仅具有弱收敛性。为了得到强收敛性,本文通过改进文献中的算法,构造了一个具有强收敛性的算法。该算法为了避免计算有界线性算子的范数,还采用了变步长策略。并且在较弱的条件下,证明了算法的强收敛性。

求解分裂可行问题的一种半空间投影算法

本文研究了分裂可行问题.利用松弛投影的方法,获得了分裂可行问题最优值点,推广了已有文献中的有关结果.

广义循环Douglas-Rachford算法

Douglas-Rachford分裂算法(DRSM)是求解两个闭凸集交的可行问题非常有效的算法。对于多个闭凸集的情形,Borwein和Tam提出了循环DRSM来求解,并证明了算法的收敛性。广义DRSM作为经典DRSM的推广,可以使得算法收敛速度更快。在本文中,我们提出使用广义循环DRSM来求解多集凸可行问题,借助均值算子的性质,我们给出了算法的收敛性。

求解分裂可行问题的一种新算法

主要对解决分裂可行问题的松驰CQ算法进行修正,设计了一种新的算法.该算法在每步迭代中应用类-Armijo搜索来获取步长,避免了矩阵逆和矩阵最大特征值的计算,而且在每步迭代中都根据当前迭代点的信息选择合适的步长,证明了该算法的全局收敛性.