Lipschitz拟伪压缩映像族的收缩投影算法

在Hilbert空间中设计了一种关于Lipschitz拟伪压缩映像族的收缩投影算法,并利用所提出的算法证明了Lipschitz拟伪压缩映像族的公共不动点的强收敛定理,所得结果改进和推广了一些最新文献的相关结果.     

Hilbert空间中Lipschitz伪压缩映像有限族公共不动点的杂交投影算法

给出了Hilbert空间中Lipschitz伪压缩映像有限族公共不动点的一个杂交投影算法,并利用所给出的杂交投影算法证明了一个强收敛定理.     

半压缩映像含误差项的Ishikawa迭代序列

本文给出了Hilbert空间上的Lipschitz半压缩映像的具有误差项的Ishikawa迭代序列收敛于不动点的充分必要条件．     

拟非扩张映像族的公共不动点的迭代方法

引入了修正的杂交投影迭代算法,用来构造Hilbert空间中拟非扩张映像族的公共不动点.使用新的算法证明了几个强收敛定理.新算法的优点是不要求映像具有次闭性质.     

Hilbert空间中k—严格伪压缩映像不动点的迭代算法

给出了Hilbert空间中k-严格伪压缩映像不动点的一个迭代算法,并利用所给出的算法证明了一个强收敛定理.     

Hilbert空间中拟非扩张非自映像的不动点的粘滞迭代方法

针对Hilbert空间中拟非扩张非自映像引入了三种新的粘滞方法,并证明了所提出的三种算法的强收敛,改进和推广了相关的结果.     

Hilbert空间中闭的拟非扩张映像不动点的迭代方法

首次引入了一种迭代算法,用以构造Hilbert空间中闭的拟非扩张映像的不动点.使用新的算法证明了一个强收敛定理.新算法的优点是不要求映像具有次闭性质.     

关于带扰动映像的广义平衡问题与k-严格伪压缩映像的不动点问题的强收敛定理

在Hilbert空间中提出一种新的迭代算法,用于寻求带扰动映像的广义平衡问题与k-严格伪压缩映像的不动点问题的公共解.此外,证明了由此迭代算法生成的序列的强收敛性.所得到的结果,推广并改进了最近一些人所发布的新结果.     

严格拟伪压缩映像族的复合迭代算法

在Hilbert空间中设计了一种关于严格拟伪压缩映像族的复合迭代算法,并利用度量投影法证明了严格拟伪压缩映像族的公共不动点的强收敛定理,所得结果改进和推广了一些最新文献的相关结果.     

无限族严格伪压缩映象的强收敛定理

对无限族严格伪压缩映像公共不动点问题,在Hilbert空间中,用CQ方法在适当的条件下,证明了一些强收敛定理,也推广和改进了最近一些人的最新结果.     

On convergence and complexity of the modified forward‐backward method involving new linesearches for convex minimization

In optimization theory, convex minimization problems have been intensively investigated in the current literature due to its wide range in applications. A major and effective tool for solving such problem is the forward‐backward splitting algorithm. However, to guarantee the convergence, it is usually assumed that the gradient of functions is Lipschitz continuous and the stepsize depends on the Lipschitz constant, which is not an easy task in practice. In this work, we propose the modified forward‐backward splitting method using new linesearches for choosing suitable stepsizes and discuss the convergence analysis including its complexity without any Lipschitz continuity assumption on the gradient. Finally, we provide numerical experiments in signal recovery to demonstrate the computational performance of our algorithm in comparison to some well‐known methods. Our reports show that the proposed algorithm has a good convergence behavior and can outperform the compared methods.     

Asymptotic error distribution for the Euler scheme with locally Lipschitz coefficients

In traditional works on numerical schemes for solving stochastic differential equations (SDEs), the globally Lipschitz assumption is often assumed to ensure different types of convergence. In practice, this is often too strong a condition. Brownian motion driven SDEs used in applications sometimes have coefficients which are only Lipschitz on compact sets, but the paths of the SDE solutions can be arbitrarily large. In this paper, we prove convergence in probability and a weak convergence result under a less restrictive assumption, that is, locally Lipschitz and with no finite time explosion. We prove if a numerical scheme converges in probability uniformly on any compact time set (UCP) with a certain rate under a global Lipschitz condition, then the UCP with the same rate holds when a globally Lipschitz condition is replaced with a locally Lipschitz plus no finite explosion condition. For the Euler scheme, weak convergence of the error process is also established. The main contribution of this paper is the proof of $\sqrt{n}$ weak convergence of the normalized error process and the limit process is also provided. We further study the boundedness of the second moments of the weak limit process and its running supremum under both global Lipschitz and locally Lipschitz conditions.     

On the United Theory of the Family of Euler—Haller Type Methods with Cubical Convergence in Banach Spaces

The convergence problem of the family of Euler-Halley methods is considered under the Lipschitz condition with the L-average,and a united convergence theory with its applications is presented.     

On the United Theory of the Family of Euler-Halley Type Methods with Cubical Convergence in Banach Spaces

The convergence problem of the family of Euler-Halley methods is considered under the Lipschitz condition with the L-average, and a united convergence theory with its applications is presented.     

Numerical Solutions of Stochastic Differential Delay Equations with Jumps

Abstract

In this article, we investigate the strong convergence of the Euler–Maruyama method and stochastic theta method for stochastic differential delay equations with jumps. Under a global Lipschitz condition, we not only prove the strong convergence, but also obtain the rate of convergence. We show strong convergence under a local Lipschitz condition and a linear growth condition. Moreover, it is the first time that we obtain the rate of the strong convergence under a local Lipschitz condition and a linear growth condition, i.e., if the local Lipschitz constants for balls of radius R are supposed to grow not faster than log R.     

SINGLE PROJECTION ALGORITHM FOR VARIATIONAL INEQUALITIES IN BANACH SPACES WITH APPLICATION TO CONTACT PROBLEM

We study the single projection algorithm of Tseng for solving a variational inequality problem in a 2-uniformly convex Banach space. The underline cost function of the variational inequality is assumed to be monotone and Lipschitz continuous. A weak convergence result is obtained under reasonable assumptions on the variable step-sizes. We also give the strong convergence result for when the underline cost function is strongly monotone and Lipchitz continuous. For this strong convergence case, the proposed method does not require prior knowledge of the modulus of strong monotonicity and the Lipschitz constant of the cost function as input parameters, rather, the variable step-sizes are diminishing and non-summable. The asymptotic estimate of the convergence rate for the strong convergence case is also given. For completeness, we give another strong convergence result using the idea of Halpern's iteration when the cost function is monotone and Lipschitz continuous and the variable step-sizes are bounded by the inverse of the Lipschitz constant of the cost function.Finally, we give an example of a contact problem where our proposed method can be applied.     

On relationship between convergence ball of euler iteration in banach spaces and its dynamical behavior on Riemann spheres

The relationship between the convergence ball of the Euler iteration in Banach Spaces and its exclusive fixed points on Riemann spheres is investigated. By using an exclusive fixed point of the Euler iteration, the convergence ball is determined accurately for a class of operators whose derivatives satisfy some generalized Lipschitz condition on Banach spaces.     

Convergence of the Gradient Sampling Algorithm on Directionally Lipschitz Functions

Set-Valued and Variational Analysis - The convergence theory for the gradient sampling algorithm is extended to directionally Lipschitz functions. Although directionally Lipschitz functions are not...     

On the complexity of extending the convergence region for Traub’s method

The convergence region of Traub’s method for solving equations is small in general. This fact limits its applicability. We locate a more precise region containing the Traub iterations leading to at least as tight Lipschitz constants as before. Our convergence analysis is finer, and obtained without additional conditions. The new theoretical results are tested on numerical examples that illustrate their superiority over earlier results.     

非全局Lipschitz条件下跳适应向后Euler方法的强收敛性分析

本文研究跳适应向后Euler方法求解跳扩散随机微分方程在非全局Lipschitz条件下的强收敛性.通过克服方程非全局Lipschitz系数给收敛性分析带来的主要困难,我们成功地建立了跳适应后向Euler方法的强收敛性结果并得到相应的收敛率.最后,我们通过数值试验对前文所得理论结果做进一步的验证.