• Title/Summary/Keyword: Hilbert inequality

Search Result 106, Processing Time 0.025 seconds

SOLVING QUASIMONOTONE SPLIT VARIATIONAL INEQUALITY PROBLEM AND FIXED POINT PROBLEM IN HILBERT SPACES

  • D. O. Peter;A. A. Mebawondu;G. C. Ugwunnadi;P. Pillay;O. K. Narain
    • Nonlinear Functional Analysis and Applications
    • /
    • v.28 no.1
    • /
    • pp.205-235
    • /
    • 2023
  • In this paper, we introduce and study an iterative technique for solving quasimonotone split variational inequality problems and fixed point problem in the framework of real Hilbert spaces. Our proposed iterative technique is self adaptive, and easy to implement. We establish that the proposed iterative technique converges strongly to a minimum-norm solution of the problem and give some numerical illustrations in comparison with other methods in the literature to support our strong convergence result.

A NEW SUBCLASS OF MEROMORPHIC FUNCTIONS DEFINED BY HILBERT SPACE OPERATOR

  • AKGUL, Arzu
    • Honam Mathematical Journal
    • /
    • v.38 no.3
    • /
    • pp.495-506
    • /
    • 2016
  • In this paper, we introduce and investigate a new subclass of meromorphic functions associated with a certain integral operator on Hilbert space. For this class, we obtain several properties like the coefficient inequality, extreme points, radii of close-to-convexity, starlikeness and meromorphically convexity and integral transformation. Further, it is shown that this class is closed under convex linear combination.

SOME CONVERGENCE THEOREM FOR AND RANDOM VARIABLES IN A HILBERT SPACE WITH APPLICATION

  • Han, Kwang-Hee
    • Honam Mathematical Journal
    • /
    • v.36 no.3
    • /
    • pp.679-688
    • /
    • 2014
  • The notion of asymptotically negative dependence for collection of random variables is generalized to a Hilbert space and the almost sure convergence for these H-valued random variables is obtained. The result is also applied to a linear process generated by H-valued asymptotically negatively dependent random variables.

SOME TRACE INEQUALITIES FOR CONVEX FUNCTIONS OF SELFADJOINT OPERATORS IN HILBERT SPACES

  • Dragomir, Silvestru Sever
    • Korean Journal of Mathematics
    • /
    • v.24 no.2
    • /
    • pp.273-296
    • /
    • 2016
  • Some new trace inequalities for convex functions of self-adjoint operators in Hilbert spaces are provided. The superadditivity and monotonicity of some associated functionals are investigated. Some trace inequalities for matrices are also derived. Examples for the operator power and logarithm are presented as well.

AN ITERATIVE METHOD FOR EQUILIBRIUM PROBLEMS, VARIATIONAL INEQUALITY PROBLEMS AND FIXED POINT PROBLEMS

  • Shang, Meijuan;Su, Yongfu
    • Journal of applied mathematics & informatics
    • /
    • v.27 no.1_2
    • /
    • pp.161-173
    • /
    • 2009
  • In this paper, we introduce an iterative scheme for finding a common element of the set of fixed points of a nonexpansive mapping, the set of solutions of the variational inequality for an inverse-strongly monotone mapping and the set of solutions of an equilibrium problem in a Hilbert space. We show that the iterative sequence converges strongly to a common element of the three sets. The results of this paper extend and improve the corresponding results announced by many others.

  • PDF

A VISCOSITY TYPE PROJECTION METHOD FOR SOLVING PSEUDOMONOTONE VARIATIONAL INEQUALITIES

  • Muangchoo, Kanikar
    • Nonlinear Functional Analysis and Applications
    • /
    • v.26 no.2
    • /
    • pp.347-371
    • /
    • 2021
  • A plethora of applications from mathematical programmings, such as minimax, mathematical programming, penalization and fixed point problems can be framed as variational inequality problems. Most of the methods that used to solve such problems involve iterative methods, that is why, in this paper, we introduce a new extragradient-like method to solve pseudomonotone variational inequalities in a real Hilbert space. The proposed method has the advantage of a variable step size rule that is updated for each iteration based on previous iterations. The main advantage of this method is that it operates without the previous knowledge of the Lipschitz constants of an operator. A strong convergence theorem for the proposed method is proved by letting the mild conditions on an operator 𝒢. Numerical experiments have been studied in order to validate the numerical performance of the proposed method and to compare it with existing methods.