In this paper, by means of the concept of attractive points of a nonlinear mapping, we prove strong convergence theorem of the Ishikawa iteration for an (α, β)−generalized hybrid mapping in a uniformly convex Banach space, and obtain weak convergence theorem of the Ishikawa iteration for such a mapping in a Hilbert space.

This paper investigates a gradient descent algorithm with penalty for a recurrent neural network. The penalty we considered here is a term proportional to the norm of the weights. Its primary roles in the methods are to control the magnitude of the weights. After proving that all of the weights are automatically bounded during the iteration process, we also present some deterministic convergenc...

In this paper, we represent an inexact inverse subspace iteration method for computing a few eigenpairs of the generalized eigenvalue problem Ax = Bx [Q. Ye and P. Zhang, Inexact inverse subspace iteration for generalized eigenvalue problems, Linear Algebra and its Application, 434 (2011) 1697-1715 ]. In particular, the linear convergence property of the inverse subspace iteration is preserved.

In this paper, we study the convergence of implicit Mann iteration processes with bounded perturbations for approximating a common fixed point of nonexpansive semigroup in CAT(0) spaces. We obtain the -convergence results of implicit Mann iteration schemes with bounded perturbations for a family of nonexpansive mappings in CAT(0) spaces. Under certain and different conditions, we also get the s...

The Krasnoselskii-Mann iteration plays an important role in the approximation of fixed points of nonexpansive operators; it is 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...

in this paper we derive convergence theorems for an -nonexpansive mappingof a nonempty closed and convex subset of a complete cat(0) space for sp-iterative process and thianwan's iterative process.

In this paper, we shall establish some strong convergence results for the recently introduced Jungck-Mann iteration process of Singh et al. [18] and the newly introduced Jungck-Ishikawa iteration process in the class of non-selfmappings in an arbitrary Banach space. Our results are generalizations and extensions of those of Berinde [4], Rhoades [13, 14] as well as some other analogous ones in t...

In this paper we introduce the Jungck-Agarwal et al. iteration procedure and obtain strong convergence as well as stability results for a pair of non-self mappings. The results obtained are generalization of some existing results in the literature. In addition, we show that the rate of convergence of this newly defined iteration procedure is better than JungckMann, Jungck-Ishikawa and JungckNoo...

| Delta coding is an iterative genetic search strategy that sustains search by periodically re-initializing the population. This helps to avoid premature convergence during genetic search. Delta coding also remaps hyper-space with each iteration in an attempt to locate \easier" search spaces with respect to genetic search. Here, the optimization ability of delta coding is compared against the C...