A Note on the Nonlinear Landweber Iteration

We reconsider the Landweber iteration for nonlinear ill-posed problems. It is known that this method becomes a regularization method in the case when the iteration is terminated as soon as the residual drops below a certain multiple of the noise level in the data. So far, all known estimates of this factor are greater than two. Here we derive a smaller factor that may be arbitrarily close to one depending on the type of nonlinearity of the underlying operator equation.     

Modified Landweber Iteration in Banach Spaces—Convergence and Convergence Rates

We introduce and discuss an iterative method of modified Landweber type for regularization of nonlinear operator equations in Banach spaces. Under smoothness and convexity assumptions on the solution space we present convergence and stability results. Furthermore, we will show that under the so-called approximate source conditions convergence rates may be achieved by a proper a-priori choice of the parameter of the presented algorithm. We will illustrate these theoretical results with a numerical example.     

A New Implicit Iteration Process with Errors for the Family of Strongly Pseudocontractive Mappings

A method is presented for generating a sequence of lower and upper bounds for the eigenvalues of the problem (i) Tu-λSu = 0, where T and S belong to a class of unbounded and nonsymmetric operators in a separable Hilbert space. Sufficient conditions are derived for the convergence of the sequence of bounds to the eigenvalues of (i), and the applicability of the method is illustrated by approximating the smallest eigenvalue of a non-selfadjoint differential eigenvalue problem.     

A modified fixed-point iterative algorithm for image restoration using fourth-order PDE model

In this paper, we propose a modified fixed point iterative algorithm to solve the fourth-order PDE model for image restoration problem. Compared with the standard fixed point algorithm, the proposed algorithm needn?t to compute inverse matrices so that it can speed up the convergence and reduce the roundoff error. Furthermore, we prove the convergence of the proposed algorithm and give some experimental results to illustrate its effectiveness by comparing with the standard fixed point algorithm, the time marching algorithm and the split Bregman algorithm.     

Total bounded variation‐based Poissonian images recovery by split Bregman iteration

This paper presents a new total bounded variation regularization‐based Poissonian images deconvolution scheme. Computationally, an extended split Bregman iteration is described to obtain the optimal solution recursively. Moreover, the rigorous convergence analysis of the proposed algorithm is also expatiated here. Compared with the computational speed and the recovered results of the total variation‐based method, numerical simulations definitely demonstrate the competitive performance of the proposed strategy in Poissonian images restoration. Copyright © 2012 John Wiley & Sons, Ltd.     

A note on the convergence of an inertial version of a diagonal hybrid projection-point algorithm

In this note, an inertial and relaxed version of a diagonal hybrid projection-proximal point algorithm is considered, in order to find the minimum of a function f approximated by a sequence of functions (in general, smoother than f or taking into account some constraints of the problem). Two convergence theorems are proved under different kind of assumptions, which allows to apply the method in various cases.     

A Mehrotra-Type Predictor-Corrector Algorithm for P*(κ) Linear Complementarity Problems

Mehrotra-type predictor-corrector algorithm,as one of most efficient interior point methods,has become the backbones of most optimization packages.Salahi et al.proposed a cut strategy based algorithm for linear optimization that enjoyed polynomial complexity and maintained its efficiency in practice.We extend their algorithm to P_*（κ）linear complementarity problems.The way of choosing corrector direction for our algorithm is different from theirs. The new algorithm has been proved to have an ο(（1+4κ）（17+19κ） √（1+2κn）^3/2log[（x⁰）^Ts⁰/ε] worst case iteration complexity bound.An numerical experiment verifies the feasibility of the new algorithm.     

块Toeplitz方程组的快速块Gauss-Seidel迭代算法

本文研究块Toeplitz方程组的块Gauss-Seidel迭代算法。我们首先讨论了块三角Toeplitz矩阵的一些性质,然后给出了求解块三角Toeplitz矩阵逆的快速算法,由此而得到了求解块Toeplitz方程组的快速块Gauss-Seidel迭代算法,最后证明了当系数矩阵为对称正定和H-矩阵时该方法都收敛,数值例子验证了方法的收敛性。