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strong convergence rate

On weak and strong convergence rate for the Heston stochastic volatility model

On weak and strong convergence rate for the Heston stochastic volatility model

... weak convergence rate of the stochastic trapezoidal rule is two, for the full parameter regime, provided the variance process is exactly ...This rate is consistent with the standard rate of ...

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Strong convergence bounds of the Hill type estimator under second order regularly varying conditions

Strong convergence bounds of the Hill type estimator under second order regularly varying conditions

... the convergence properties of the estimators for ...The convergence properties of the Pickands estimator such as consistency, asymptotic normality and the strong convergence rate have ...

7

Strong convergence theorem of a new iterative method for weak contractions and comparison of the rate of convergence in Banach space

Strong convergence theorem of a new iterative method for weak contractions and comparison of the rate of convergence in Banach space

... prove strong convergence theorem of the proposed method under some control ...the rate of convergence between the Noor iteration and our ...Keywords: strong convergence; ...

10

Multi step implicit iterative methods with regularization for minimization problems and fixed point problems

Multi step implicit iterative methods with regularization for minimization problems and fixed point problems

... Recently, motivated by the work of Takahashi and Zembayashi [], Cholamjiak [] in- troduced a new hybrid projection algorithm for finding a common element of the set of solutions of the equilibrium problem and the set of ...

26

Implicit iteration process of nonexpansive non self mappings

Implicit iteration process of nonexpansive non self mappings

... the convergence of the sequences { x n } , { y n } , { z n } satisfying x n = (1 − α n )u + α n T [(1 − β n )x n + β n Tx n ], y n = (1 − α n )u + α n PT[(1 − β n )y n + β n PT y n ...

8

Mathematical programming for the sum of two convex functions with applications to lasso problem, split feasibility problems, and image deblurring problem

Mathematical programming for the sum of two convex functions with applications to lasso problem, split feasibility problems, and image deblurring problem

... method to study the split feasibility problem in finite dimensional spaces, but in the in- finite dimensional Hilbert space, a strong convergence theorem may not be true for the split feasibility problem by ...

23

An algorithm for approximating a common fixed point of a finite family of Lipschitz pseudocontractive multi-valued mappings

An algorithm for approximating a common fixed point of a finite family of Lipschitz pseudocontractive multi-valued mappings

... Abstract. The purpose of this paper is twofold. We first give erratum to a proof given by Woldeamanuel et al. [Strong convergence theorems for a common fixed point of a finite family of Lipschitz ...

27

Strong and  Convergence Theorems for Multivalued Mappings in  Spaces

Strong and Convergence Theorems for Multivalued Mappings in Spaces

... show strong and Δ convergence for Mann iteration of a multivalued nonexpansive mapping whose domain is a nonempty closed convex subset of a CAT0 ...2008. Strong convergence of Ishikawa ...

16

Strong convergence of approximated iterations for asymptoticallypseudocontractive mappings

Strong convergence of approximated iterations for asymptoticallypseudocontractive mappings

... This work contains our dedicated study to develop and improve iterative algorithms for finding the fixed points of asymptotically pseudocontractive mappings in Hilbert spaces. We introduced our iterative algorithm for this ...

13

Approximation of zeros of bounded maximal monotone mappings, solutions of Hammerstein integral equations and convex minimization problems

Approximation of zeros of bounded maximal monotone mappings, solutions of Hammerstein integral equations and convex minimization problems

... Within the past  years or so, methods for approximating solutions of equation (.) when A is an accretive-type operator have become a flourishing area of research for nu- merous mathematicians. Numerous ...

28

A new algorithm for variational inequality problems with alpha-inverse strongly monotone maps and common fixed points for a countable family of relatively weak nonexpansive maps, with applications

A new algorithm for variational inequality problems with alpha-inverse strongly monotone maps and common fixed points for a countable family of relatively weak nonexpansive maps, with applications

... Remark 1. In L p spaces, 1 < p < ∞, p 6= 2, the normalized duality map J is not weakly sequen- tially continuous and so the theorem of Iiduka and Takahashi [22], may not be applicable, since in this theorem J is ...

25

Asymptotic Properties of Optimized Type CVaR Estimator for NA Random Variables

Asymptotic Properties of Optimized Type CVaR Estimator for NA Random Variables

... the strong consistency and asymptotic normality under the * -mixing samples, and its convergence ...the strong consistency under the + -mixing sample, and gave the rate of ...

8

Rate of Convergence in Sobolev Space

Rate of Convergence in Sobolev Space

... Some properties of approximation of functions of two variable by Bernstein -Chlodowsky poly- nomials was proven in [1]-[5] and [7]. In addition, convergence of Bernstein-Chlodowsky polynomials of two variables ...

5

Strong Convergence of an Implicit Algorithm in CAT(0) Spaces

Strong Convergence of an Implicit Algorithm in CAT(0) Spaces

... their strong convergence play an important role in finding a common element of the set of fixed common fixed point for different classes of mappings and the set of solutions of an equilibrium problem in the ...

11

Strong convergence of iterative algorithms for the split equality problem

Strong convergence of iterative algorithms for the split equality problem

... equality problem (SEP) is finding x ∈ C, y ∈ Q such that Ax = By. Recently, Moudafi has presented the ACQA algorithm and the RACQA algorithm to solve SEP. However, the two algorithms are weakly convergent. It is therefore ...

19

Strong convergence of a modified proximal algorithm for solving the lasso

Strong convergence of a modified proximal algorithm for solving the lasso

... In this paper, based on the viscosity iterative algorithm (.), we propose a modified formulation of the proximal algorithm (.). It is proved that the algorithm we propose can obtain strong convergence. ...

15

Strong convergence of a general iterative algorithm in Hilbert spaces

Strong convergence of a general iterative algorithm in Hilbert spaces

... In this paper, based on a general iterative algorithm, we study the problem of approx- imating a common element in the common fixed point set of an infinite family of non- expansive mappings, in the solution set of a ...

18

Strong convergence theorems for fixed points of nonlinear mappings

Strong convergence theorems for fixed points of nonlinear mappings

... Huang, Strong convergence theorems for fixed point problems and generalized equilibrium problems of three relatively quasi-nonexpansive mappings in Banach spaces, J. Kang, Convergence th[r] ...

8

A strong convergence theorem of common elements in Hilbert spaces

A strong convergence theorem of common elements in Hilbert spaces

... Recently, many authors studied the problems (.), (.) and (.) based on hybrid pro- jection methods; see, for example, [–] and the references therein. Motivated by these results, we investigated the common ...

16

Strong convergence of a splitting algorithm for treating monotone operators

Strong convergence of a splitting algorithm for treating monotone operators

... weak convergence of PPA, many authors considered lots of different modifications; see [–] the references ...obtained strong convergence theorems in Hilbert space without any compact assumption but ...

15

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