• The Pure and Applied Mathematics
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• v.27 no.1
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• pp.61-70
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• 2020

In this paper, we introduce a new concept of stability of coincidence iterative algorithm for three mappings and derive a new three-step Jungck-type iterative algorithm. And, we prove a stability result and a strong convergence result for the Jungck-type algorithm using the M_J-contractive condition. Our results extend and unify the corresponding ones in [3, 6, 7, 13].

• The Journal of Korean Association of Computer Education
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• v.19 no.1
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• pp.101-109
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• 2016

Designing algorithms is a very important learning process in computational thinking education because it requires learner's logical and procedural thinking. But the case studies that have topics of algorithms learning and students' types of errors in learning algorithms are not enough. So the purpose of this study is to analyze students' errors that discovered in the process of learning three control structures of programming using flowchart and provide types of errors in designing algorithms. Results about tests of three types of control structures in university student's algorithms learning class showed different cases of types of errors; types of sequential control error are not presented in the class, types of conditional control error are presented in the case of setting the conditions of nested conditional control, and types of iterative control are showed in the many cases of iterative conditions, statements of single and nested iterative control structure. The results of study will be a good case study about teaching designing algorithms of computational thinking education in elementary, secondary school and university.

• Korean Journal of Optics and Photonics
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• v.11 no.1
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• pp.47-57
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• 2000

A two-stage iterative Fourier transform algorithm, based on hybrid input-output algorithm and new Pnoise algorithm, is used to design continuous and quantized phase-only diffractive pattern elements which produce arbitrary given intensity patterns via Fraunhofer diffraction. Numerical results for two $128\times128$ binary patterns and two grayscale patterns are compared with those of other algorithms. It is found that the algorithm yields better signal-to-noise ratio and even better uniformity with slightly lower diffraction efficiency than other algorithms. We investigated the dependence of performance on parameters used in the algorithm, size of noise region, and the number of phase levels for quantized elements. In the case of quantized phase elements, the size of noise region plays a greater role in determining the performance of the algorithm than given intensity pattern itself. tself.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.2
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• pp.247-252
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• 2004

In this paper are proposed 2nd-order PD-type iterative learning control algorithms for linear continuous-time system and linear discrete-time system. In contrast to conventional methods, the proposed learning algorithms are constructed based on both time-domain performance and iteration-domain performance. The convergence of the proposed learning algorithms is proved. Also, it is shown that the proposed method has robustness in the presence of external disturbances and the convergence accuracy can be improved. A numerical example is provided to show the effectiveness of the proposed algorithms.

• Honam Mathematical Journal
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• v.14 no.1
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• pp.107-121
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• 1992

In this paper, we consider an iterative algorithm for solving a new class of quasi complementarity problems of finding $u{\epsilon}R^{n}$ such that $g(u){\in}K(u)$, $Tu+A(u){\in}K^{*}(u)$, and < g(u), Tu + A(u) >=0, where T, A and g are continuous mappings from $R^{n}$ into itself and $K^{*}(u)$ is the polar cone of the convex cone K(u) in $R^{n}$. The algorithms considered in this paper are general and unifying ones, which include many existing algorithms as special cases for solving the complementarity problems. We also study the convergence criteria of the general algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.12
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• pp.739-745
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• 2014

It has been shown in compressive sensing that every s-sparse $x{\in}R^N$ can be recovered from the measurement vector y=Ax or the noisy vector y=Ax+e via ${\ell}_1$-minimization as soon as the 3s-restricted isometry constant of the sensing matrix A is smaller than 1/2 or smaller than $1/\sqrt{3}$ by applying the Iterative Hard Thresholding (IHT) algorithm. However, recovery can be guaranteed by practical algorithms for some certain assumptions of acquisition schemes. One of the key assumption is that the sensing matrix must satisfy the Restricted Isometry Property (RIP), which is often violated in the setting of many practical applications. In this paper, we studied a generalization of RIP, called Restricted Biorthogonality Property (RBOP) for anisotropic cases, and the new recovery algorithms called oblique pursuits. Then, we provide an analysis on the success of sparse recovery in terms of restricted biorthogonality constant for the IHT algorithms.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1363-1379
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• 2011

Halpern iterative algorithm is one of the most cited in the literature of approximation of fixed points of nonexpansive mappings. Different authors modified this iterative algorithm in Banach spaces to approximate fixed points of nonexpansive mappings. One of which is Hu [8] and Yao et al [21] modification of Halpern iterative algorithm for nonexpansive mappings in Banach spaces. It is the purpose of this paper to thoroughly analyze this modification and its convergence conditions. Unfortunately, Hu [8] and Yao et al [21] control conditions imposed on the modified Halpern iterative algorithm to have strong convergence are found to be not sufficient. In this paper, counterexamples are constructed to prove that the strong convergence conditions of Hu [8] and Yao et al [21] are not sufficient. It is also proved that with some additional conditions on the control parameters, strong convergence of the defined iterative algorithm is obtained in different Banach space settings.

• Communications of the Korean Mathematical Society
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• v.28 no.2
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• pp.243-267
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• 2013

This paper is dedicated to study a new class of general nonlinear random A-maximal $m$-relaxed ${\eta}$-accretive (so called (A, ${\eta}$)-accretive [49]) equations with random relaxed cocoercive mappings and random fuzzy mappings in $q$-uniformly smooth Banach spaces. By utilizing the resolvent operator technique for A-maximal $m$-relaxed ${\eta}$-accretive mappings due to Lan et al. and Chang's lemma [13], some new iterative algorithms with mixed errors for finding the approximate solutions of the aforesaid class of nonlinear random equations are constructed. The convergence analysis of the proposed iterative algorithms under some suitable conditions are also studied.

• Journal of Biomedical Engineering Research
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• v.8 no.2
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• pp.151-160
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• 1987

An algorithm is suggested that truncted projection among the incomplete projections can be recovered from non-iterative extrapolation matrix by band-limited function. After the image being reconstructed from the recovered signals by non-iterative extrapolation, a known controur information and reprojection algorithm are used. It is shown that the reconstructed image using these algorithms is close to the original image. The effectiveness for these algorithms is proved by computer simulation.

• Communications of the Korean Mathematical Society
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• v.25 no.1
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• pp.129-137
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• 2010

In this paper, we introduce and study a system of nonlinear set-valued implicit variational inclusions (SNSIVI) with relaxed cocoercive mappings in real Banach spaces. By using resolvent operator technique for M-accretive mapping, we construct a new class of iterative algorithms for solving this class of system of set-valued implicit variational inclusions. The convergence of iterative algorithms is proved in q-uniformly smooth Banach spaces. Our results generalize and improve the corresponding results of recent works.