Weak and Strong Density of Compositions

The convergence in various topologies of sequences of inner superposition (composition) operators acting between Lebesgue spaces and of their linear combinations is studied. In particular, the sequential density results for the linear span of such operators is proved for the weak, weak continuous and strong operator topologies.

     

REALIZATION OF PEETRE K-MODULUS ON THE SPHERE

1IntroductionandNotationsLetfi={p=(x,yiz)ER3,IPI=1}betheunitsphereintheEuclideanspaceR3.ByC(O)andLP(O),1SP相似文献   

Super and weak Poincaré inequalities for hypoelliptic operators

Sufficient conditions are presented for super/weak Poincare inequalities to hold for a class of hypoelliptic operators on noncompact manifolds. As applications, the essential spectrum and the convergence rate of the associated Markov semigroup are described for Gruschin type operators on R2 and Kohn-Laplacian type operators on the Heisenberg group.     

On split common fixed point problems

Based on the convergence theorem recently proved by the second author, we modify the iterative scheme studied by Moudafi for quasi-nonexpansive operators to obtain strong convergence to a solution of the split common fixed point problem. It is noted that Moudafi's original scheme can conclude only weak convergence. As a consequence, we obtain strong convergence theorems for split variational inequality problems for Lipschitz continuous and monotone operators, split common null point problems for maximal monotone operators, and Moudafi's split feasibility problem.     

Generalized iterative process and associated regularization for J-Pseudomonotone mixed variational inequalities

A generalized iterative process for solving mixed variational inequalities with J-Pseudomonotone operators in uniformly smooth Banach spaces is proposed and its weak convergence is established. An application to the stationary filtration problem is given. For such variational inequalities, a generalized iterative regularization method is constructed and its weak convergence under the assumption that the iterative parameter may vary from step to step is analyzed. Our results extend and generalize the corresponding theorems of [A.M. Saddeek, S.A. Ahmed, Convergence analysis of iterative methods for some variational inequalities with J-Pseudomonotone operators in uniformly smooth Banach spaces, Appl. Sci. Comput., accepted for publication, A.M. Saddeek, S.A. Ahmed, On the convergence of some iteration processes for J-Pseudomonotone mixed variational inequalities in uniformly smooth Banach spaces, Math. Comput. Modell., 46(3-4) (2007) 557-572].     

Asymptotic behavior of resolvents of coaccretive operators in the Hilbert ball

We study the resolvents of coaccretive operators in the Hilbert ball, with special emphasis on the asymptotic behavior of their compositions and metric convex combinations. We consider the case where the given coaccretive operators share a common fixed point inside the ball, as well as the case where they share a common sink point on its boundary. We establish weak convergence in the former case and strong convergence in the latter. We also present two related convergence results for a continuous implicit scheme.     

Piecewise linear least squares approximations of Frobenius-Perron operators

We propose a piecewise linear numerical method based on least squares approximations for computing stationary density functions of Frobenius-Perron operators associated with piecewise C² and stretching mappings of the unit interval. We prove the weak convergence of the method for a class of Frobenius-Perron operators, and the numerical results show that it is also norm convergent and has a better convergence rate than the piecewise linear Markov approximation method.     

Properties of subspaces of the space of affine functions

Conditions are presented for weak (strong) convergence, in the entire space A(x), of a sequence of positive operators to a fixed operator S on the basis of its weak (strong) convergence to S in a subspace. The criterion of Bauer's simplex is presented.Translated from Matematicheskie Zametki, Vol. 17, No. 2, pp. 307–318, February, 1975.In conclusion the author expresses his deep gratitude to Yu. A. Shashkin for his many valuable remarks.     

A note on quadratic forms of stationary functional time series under mild conditions

We study distributional properties of a quadratic form of a stationary functional time series under mild moment conditions. As an important application, we obtain consistency rates of estimators of spectral density operators and prove joint weak convergence to a vector of complex Gaussian random operators. Weak convergence is established based on an approximation of the form via transforms of Hilbert-valued martingale difference sequences. As a side-result, the distributional properties of the long-run covariance operator are established.     

下降算子和弱压缩算子的一般理论及其应用

函数或泛函求极大极小(或最大最小)的问题,在数值计算中是经常遇到的.许多计算问题往往都导致所谓“极小化”问题.例如,各种最优逼近问题.矛盾方程组求最小偏差解以及最优化计算等.为解决这些问题提出了各种各样的迭代算法.从形式上看他们各自大不相同,并根据具体情况采用各自不同的方法证明其收敛性.本文引进了度量空间中的“下降算子”及“弱压缩算子”的概念,它们在某种意义上概括了上述这些形式不同的各     

Strong convergence of the forward–backward splitting method with multiple parameters in Hilbert spaces

Many problems arising from machine learning, signal & image recovery, and compressed sensing can be casted into a monotone inclusion problem for finding a zero of the sum of two monotone operators. The forward–backward splitting algorithm is one of the most powerful and successful methods for solving such a problem. However, this algorithm has only weak convergence in the infinite dimensional settings. In this paper, we propose a new modification of the FBA so that it possesses a norm convergent property. Moreover, we establish two strong convergence theorems of the proposed algorithms under more general conditions.     

Rate of approximation for functions of bounded variation by integral operators

We estimate pointwise convergence rates of approximation for functions of bounded variation and for functions which are exponentially bounded and locally of bounded variation. The approximation is through the operation of a sequence of integral operators with not necessarily positive kernel functions. The general result is then applied to deduce estimates for particular operators, such as Beta operators, Fourier–Legendre operators, Picard operators, and Gauss–Weierstrass operators.     

Generalized Krasnoselskii–Mann-type iterations for nonexpansive mappings in Hilbert spaces

The Krasnoselskii–Mann iteration plays an important role in the approximation of fixed points of nonexpansive operators; it is known to be weakly convergent in the infinite dimensional setting. In this present paper, we provide a new inexact Krasnoselskii–Mann iteration and prove weak convergence under certain accuracy criteria on the error resulting from the inexactness. We also show strong convergence for a modified inexact Krasnoselskii–Mann iteration under suitable assumptions. The convergence results generalize existing ones from the literature. Applications are given to the Douglas–Rachford splitting method, the Fermat–Weber location problem as well as the alternating projection method by John von Neumann.     

Relaxed two points projection method for solving the multiple-sets split equality problem

The multiple-sets split equality problem, a generalization and extension of the split feasibility problem, has a variety of specific applications in real world, such as medical care, image reconstruction, and signal processing. It can be a model for many inverse problems where constraints are imposed on the solutions in the domains of two linear operators as well as in the operators’ ranges simultaneously. Although, for the split equality problem, there exist many algorithms, there are but few algorithms for the multiple-sets split equality problem. Hence, in this paper, we present a relaxed two points projection method to solve the problem; under some suitable conditions, we show the weak convergence and give a remark for the strong convergence method in the Hilbert space. The interest of our algorithm is that we transfer the problem to an optimization problem, then, based on the model, we present a modified gradient projection algorithm by selecting two different initial points in different sets for the problem (we call the algorithm as two points algorithm). During the process of iteration, we employ subgradient projections, not use the orthogonal projection, which makes the method implementable. Numerical experiments manifest the algorithm is efficient.     

Bernstein-type operators in Chebyshev spaces

We prove that it is possible to construct Bernstein-type operators in any given Extended Chebyshev space and we show how they are connected with blossoms. This generalises and explains a recent result by Aldas/Kounchev/Render on exponential spaces. We also indicate why such operators automatically possess interesting shape preserving properties and why similar operators exist in still more general frameworks, e.g., in Extended Chebyshev Piecewise spaces. We address the problem of convergence of infinite sequences of such operators, and we do prove convergence for special instances of Müntz spaces.      

On Convergence of One-Step Schemes for Weak Solutions of Quantum Stochastic Differential Equations

Several one-step schemes for computing weak solutions of Lipschitzian quantum stochastic differential equations (QSDE) driven by certain operator-valued stochastic processes associated with creation, annihilation and gauge operators of quantum field theory are introduced and studied. This is accomplished within the framework of the Hudson–Parthasarathy formulation of quantum stochastic calculus and subject to the matrix elements of solution being sufficiently differentiable. Results concerning convergence of these schemes in the topology of the locally convex space of solution are presented. It is shown that the Euler–Maruyama scheme,with respect to weak convergence criteria for Itô stochastic differential equation is a special case of Euler schemes in this framework. Numerical examples are given.     

Fixed-Point Methods for a Certain Class of Operators

We introduce in this paper a new class of nonlinear operators, which contains, among others, the class of operators with semimonotone additive inverse and also the class of nonexpansive mappings. We study this class and discuss some of its properties. Then we present iterative procedures for computing fixed points of operators in this class, which allow for inexact solutions of the subproblems and relative error criteria. We prove weak convergence of the generated sequences in the context of Hilbert spaces. Strong convergence is also discussed.     

Introduction to the Theory of Two-Scale Convergence

Basic properties of weak and strong two-scale convergence are established for Lebesgue and Sobolev spaces, in particular, those with periodic measures depending on a small parameter. These results are applied to the homogenization of elliptic operators and spectral problems.     

Rates of Ideal Convergence for Approximation Operators

In this paper, we study a general Korovkin-type approximation theory by using the notion of ideal convergence which includes many convergence methods, such as, the usual convergence, statistical convergence, A-statistical convergence, etc. We mainly compute the rate of ideal convergence of sequences of positive linear operators.