• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.397-404
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• 2002

In this paper, it is proposed wavelet neural network using the fuzzy concept with the fuzzy and the multi-resolution analysis(MRA) of wavelet transform. Also, it wishes to improve any nonlinear function learning approximation using this system. Here, the fuzzy concept is used the bell type fuzzy membership function. And the composition of wavelet has a unit size. It is used the backpropagation algorithm for learning of wavelet neural network using the fuzzy concept. It is used the multi-resolution analysis of wavelet transform, the bell type fuzzy membership function and the backpropagation algorithm for learning. This structure is confirmed to be improved approximation performance than the conventional algorithms from one dimension and two dimensions function through simulation.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.05a
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• pp.96-102
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• 2004

This study presents an effective stiffness-based optimal technique to control quantitatively lateral drift for 3-D steel frameworks subject to lateral loads. To this end, the displacement sensitivity depending on behavior characteristics of 3-D steel frameworks is established. Also, approximation concept that can preserve the generality of the mathematical programming and can efficiently solve large scale problems is introduced. Resizing sections in the stiffness-based optimal design are assumed to be uniformly varying in size. Two types of 30-story frames are presented to illustrate the features of the Quantitative lateral drift control technique proposed in this study.

• Kyungpook Mathematical Journal
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• v.59 no.4
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• pp.679-688
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• 2019

In the present note, we study some approximation properties of the Szász type operators based on Charlier polynomials introduced by S. Varma and F. Taşdelen (Math. Comput. Modelling, 56 (5-6) (2012) 108-112). We establish the rates of A-statistical convergence of these operators. Finally, we prove a Voronovskaja type approximation theorem and local approximation theorem via the concept of A-statistical convergence.

• Nonlinear Functional Analysis and Applications
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• v.27 no.2
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• pp.223-232
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• 2022

The purpose of the paper is to define f-projection operator to develop the f-projection method. The existence of a variational inequality problem is studied using fixed point theorem which establishes the existence of f-projection method. The concept of ρ-projective operator and σ-involutory operator are defined with suitable examples. The relation in between ρ-projective operator and σ-involutory operator are shown. The concept of σ-involutory variational inequality problem is defined and its existence theorem is also established.

• Communications of Mathematical Education
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• v.23 no.3
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• pp.625-642
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• 2009

In the school mathematics the concept of tangent is introduced in several steps in suitable contexts. Students are required to reflect and revise their concepts of tangent in order to apply the improved concept to wider range of contexts. In this paper we consider the tangent as the optimal linear approximation to a curve at a given point and make three discussions on pedagogical aspects of it. First, it provides a method of finding roots of real numbers which can be used as an application of tangent. This may help students improve their affective variables such as interest, attitude, motivation about the learning of tangent. Second, this concept reflects the modern point of view of tangent, the linear approximation of nonlinear problems. Third, it gives precise meaning of two tangent lines appearing two sides of a cusp point of a curve.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.208-215
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• 2015

Since upper and lower approximations could be induced from the rough set structures, rough sets are considered as approximations. The concept of fuzzy rough sets was proposed by replacing crisp binary relations with fuzzy relations by Dubois and Prade. In this paper, we introduce and investigate some properties of intuitionistic fuzzy rough approximation operators and intuitionistic fuzzy relations by means of topology.

• International Journal of Reliability and Applications
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• v.13 no.2
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• pp.71-80
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• 2012

This paper introduces a new approach for evaluating reliability of a complex system in terms of distributional parameters where analytical determination of reliability is intractable. The concept of discrete approximation, reported in the literature so far, fails to meet the latter requirement in terms of distributional parameters. The current work aims at offering a bound based approach where reliability planners not only get a clear idea about the extent of error but also can manipulate in terms of distributional parameters. This reliability approximation has been under taken under the Weibull frame work which is the most widely used model for reliability analysis. Numerical study has been carried out to examine the strength of our proposed reliability approximation via closeness between the two reliability bounds. This approach will be very useful during the early stages of product design as the distributional parameters can be adjusted.

• Journal of Korea Multimedia Society
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• v.22 no.10
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• pp.1160-1167
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• 2019

Because of the dynamic range limitation of digital equipment, it is impossible to obtain dark and bright areas at the same time with one shot. In order to solve this problem, an exposure fusion technique for fusing a plurality of images photographed at different exposure amounts into one is being studied. Among them, Laplacian pyramid decomposition based fusion method can generate natural HDR image by fusing images of various scales. But this requires a lot of computation time. Therefore, in this paper, we propose an approximation technique that achieves similar performance and greatly shortens computation time. The concept of vanishing point image for approximation is introduced, and the validity of the proposed approach is verified by comparing the computation time with the resultant image.

• Journal of Sensor Science and Technology
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• v.28 no.4
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• pp.240-245
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• 2019

Phase interpolation is widely adopted in frequency synthesizers and clock-and-data recovery systems to produce an intermediate phase from two existing phases. The intermediate phase is typically generated by combining two input phases with different weights. Unfortunately, this results in non-uniform phase steps. Alternatively, the intermediate phase can be generated by successive approximation, where the interpolated phase at each approximation stage is obtained using the same weight for the two intermediate phases. As a proof of concept, this study presents a 2-GHz 8-bit successive approximation digital-to-phase converter that is designed using 65-nm CMOS technology. The converter receives an 8-phase clock signal as input, and the most significant bit (MSB) section selects four phases to create two sinusoidal waveforms using a harmonic rejection filter. The remaining least significant bit (LSB) section applies the successive approximation to generate the required intermediate phase. Monte-Carlo simulations show that the proposed converter exhibits 0.46-LSB integral nonlinearity and 0.31-LSB differential nonlinearity with a power consumption of 3.12 mW from a 1.2-V supply voltage.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.10a
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• pp.141-148
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• 2000

In system design, it is not always possible that all decision makers can cooperate fully and thus avoid conflict. They each control a specified subset of design variables and seek to minimize their own cost functions subject to their individual constraints. However, a system management team makes every effort to coordinate multiple disciplines and overcome such noncooperative environment. Although full cooperation is difficult to achieve, noncooperation also should be avoided as possible. Our approach is to predict the results of their cooperation and generate approximate Pareto set for their multiple objectives. The Pareto set can be obtained according to the degree of one's conceding coupling variables in the other's favor. We employ approximation concept for modelling this coordination and the mutiobjective genetic algorithm for exploring the coupling variable space for obtaining an approximate Pareto set. The approximation management concept is also used for improving the accuracy of the Pareto set. The exploration for the coupling variable space is more efficient because of its smaller dimension than the design variable space. Also, our approach doesn't force the disciplines to change their own way of running analysis and synthesis tools. Since the decision making process is not sequential, the required time can be reduced comparing to the existing multidisciplinary optimization techniques. This approach is applied to some mathematical examples and structural optimization problems.