• 대한수학회지
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• 제33권4호
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• pp.865-878
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• 1996

We consider numerical methods for finding a solution to a nonlinear system of algebraic equations $$ (1) f(x) = 0, $$ where the function $f : R^n \to R^n$ is ain $x \in R^n$. In [10], a quasi-Gauss-Newton method is proposed and shown the computational efficiency over SQRT algorithm by numerical experiments. The convergence rate of the method has not been proved theoretically. In this paper, we show theoretically that the iterate $x_k$ obtained from the quasi-Gauss-Newton method for the problem (1) actually converges to a root by Kantorovich-type convergence analysis. We also show the rate of convergence of the method is superlinear.

• Carbon letters
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• 제22권
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• pp.101-104
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• 2017

• Journal of applied mathematics & informatics
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• 제29권5_6호
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• pp.1351-1361
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• 2011

We in this paper study the complete convergence and almost surely convergence for arrays of rowwise pairwise negatively dependent(ND) random variables (r.${\upsilon}$.'s) which are dominated randomly by some random variables and obtain a result dealing with complete convergence of linear processes.

• Journal of applied mathematics & informatics
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• 제22권1_2호
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• pp.351-360
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• 2006

In this paper, we develop an inexact-Newton method for solving nonsmooth operator equations in infinite-dimensional spaces. The linear convergence and superlinear convergence of inexact-Newton method under some conditions are shown. Then, we characterize the order of convergence in terms of the rate of convergence of the relative residuals. The present inexact-Newton method could be viewed as the extensions of previous ones with same convergent results in finite-dimensional spaces.

• 호남수학학술지
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• 제43권3호
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• pp.417-431
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• 2021

In this study, we introduced the notions of rough statistical convergence and defined the set of rough statistical limit points of a sequence and obtained statistical convergence criteria associated with this set in 2-normed space. Then, we proved that this set is closed and convex in 2-normed space. Also, we examined the relations between the set of statistical cluster points and the set of rough statistical limit points of a sequence in 2-normed space.

• Journal of applied mathematics & informatics
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• 제39권3_4호
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• pp.303-319
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• 2021

In this paper, we introduce the concepts of Wijsman strongly p-lacunary summability of order 𝛼, Wijsman lacunary statistical convergence of order 𝛼 and Hausdorff lacunary statistical convergence of order 𝛼 for double set sequences. Also, we investigate some properties of these new concepts and examine the existence of some relationships between them. Furthermore, we study the relationships between these new concepts and some concepts in the literature.

• Journal of applied mathematics & informatics
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• 제40권3_4호
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• pp.433-444
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• 2022

In the present paper, we introduce some new notions of Wijsman ${\mathcal{I}}$-statistical convergence with the use of Orlicz function, lacunary sequence and triple sequences of sets, and obtain some analogous results from the new definitions point of views.

• Journal of applied mathematics & informatics
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• 제40권1_2호
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• pp.69-83
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• 2022

We investigate the concept of lacunary statistical convergence and lacunary strongly convergence for sequence of sets in intuitionistic fuzzy metric space (IFMS) and examine their characterization. We obtain some inclusion relation relating to these concepts. Further some necessary and sufficient conditions for equality of the sets of statistical convergence and lacunary statistical convergence for sequence of sets in IFMS have been established. The concept of strong Cesàro summability in IFMS has been defined and some results are established.

• Journal of applied mathematics & informatics
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• 제40권3_4호
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• pp.619-632
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• 2022

In this study, we examine rough ${\Delta}\mathcal{I}$-statistical convergence for difference sequences as an extension of rough convergence. We investigate the set of rough ${\Delta}\mathcal{I}$-statistical limit points of a difference sequence and analyze the results with proofs.

• Journal of applied mathematics & informatics
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• 제42권2호
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• pp.245-256
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• 2024

This article introduces the notion of almost deferred weighted convergence, statistical deferred weighted almost convergence and almost deferred weighted statistical convergence for real valued sequences. Further, with the aid of interesting examples, we investigated some relationships among our proposed methods. Moreover, we prove a new type of approximation theorem and demonstrated that our theorem effectively extends and improves most of the earlier existing results. Finally, we have presented an example which proves that our theorem is a stronger than its classical versions.