• Korean Journal of Mathematics
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• 제22권4호
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• pp.699-709
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• 2014

In the present paper, we investigate starlikeness conditions for q-differential operator by using the concept of quantum calculus in the unit disk.

• Journal of applied mathematics & informatics
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• 제32권1_2호
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• pp.211-225
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• 2014

A new class of smoothing functions is introduced in this paper, which includes some important smoothing complementarity functions as its special cases. Based on this new smoothing function, we proposed a smoothing Newton method. Our algorithm needs only to solve one linear system of equations. Without requiring the nonemptyness and boundedness of the solution set, the proposed algorithm is proved to be globally convergent. Numerical results indicate that the smoothing Newton method based on the new proposed class of smoothing functions with ${\theta}{\in}(0,1)$ seems to have better numerical performance than those based on some other important smoothing functions, which also demonstrate that our algorithm is promising.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 한국지능정보시스템학회 2007년도 추계학술대회
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• pp.592-601
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• 2007

In the conventional double auction approaches, two basic assumptions are usually applied - (1) each trader has a linear or quasi-linear utility function of price and quantity, (2) buyers as well as sellers have identical utility functions. However, in practice, these assumptions are unrealisitc. Therefore, a flexible and integrated double auction mechanism that can integrate all traders' diverse utility functions is necessary. We propose a double auction mechanism with resource allocation based on nonlinear utility functions, namely a flexible synchronous double auction system where each participant can express a diverse utility function on the price and quantity. In order to optimize the total market utility consists of multiple complex utility functions of traders, our study proposes a genetic algorithm (GA) We show the viability of the proposed mechanism through several simulation experiments.

• Bulletin of the Korean Mathematical Society
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• 제61권3호
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• pp.671-697
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• 2024

In this paper, we formally introduce the notion of a general parametric digamma function Ψ(−s; A, a) and we find the Laurent expansion of Ψ(−s; A, a) at the integers and poles. Considering the contour integrations involving Ψ(−s; A, a), we present some new identities for infinite series involving Dirichlet type parametric harmonic numbers by using the method of residue computation. Then applying these formulas obtained, we establish some explicit relations of parametric linear Euler sums and some special functions (e.g. trigonometric functions, digamma functions, Hurwitz zeta functions etc.). Moreover, some illustrative special cases as well as immediate consequences of the main results are also considered.

• Journal of the Korean Mathematical Society
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• 제54권1호
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• pp.319-357
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• 2017

There are presented certain results on extending continuous linear operators defined on spaces of E-valued continuous functions (defined on a compact Hausdorff space X) to linear operators defined on spaces of E-valued measurable functions in a way such that uniformly bounded sequences of functions that converge pointwise in the weak (or norm) topology of E are sent to sequences that converge in the weak, norm or weak* topology of the target space. As an application, a new description of uniform closures of convex subsets of C(X, E) is given. Also new and strong results on integral representations of continuous linear operators defined on C(X, E) are presented. A new classes of vector measures are introduced and various bounded convergence theorems for them are proved.

• Proceedings of the KIEE Conference
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• 대한전기학회 2004년도 심포지엄 논문집 정보 및 제어부문
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• pp.13-15
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• 2004

In this paper, we propose a novel stability criterion and a guideline of controller design for switched linear systems. Unlike existing criterions such as Lie algebraic method and multiple Lyapunov functions method, the proposed criterion can be applied to each individual system without considering an overall system. By applying the proposed criterion to each individual system separately, a state feedback controller can be easily designed. Stability of the overall system is proved by developing a rule to determine non-increasing Lyapunov functions recursively at each switching instant. An illustrative example is given.

• Proceedings of the KIEE Conference
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.20-22
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• 2005

In this paper, we propose a novel stability criterion for switched linear systems. The proposed method employs the results on the upper bound of the solution of LME(Lyapunov Matrix Equation) and on the stability of hybrid system. The former guarantees the existence of Lyapunov-like energy functions and the latter shows that the stability of switched linear systems by using these energy functions. The proposed criterion releases the restriction on the stability of switched linear systems comparing with the existing methods and provides us with easy implementation way for pole assignment.

• The Journal of the Korea Contents Association
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• 제21권3호
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• pp.616-625
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• 2021

Deep neural networks are an approximation method that approximates an arbitrary function to a linear model and then repeats additional approximation using a nonlinear active function. In this process, the method of evaluating the performance of approximation uses the loss function. Existing in-depth learning methods implement approximation that takes into account loss functions in the linear approximation process, but non-linear approximation phases that use active functions use non-linear transformation that is not related to reduction of loss functions of loss. This study proposes parametric activation functions that introduce scale parameters that can change the scale of activation functions and location parameters that can change the location of activation functions. By introducing parametric activation functions based on scale and location parameters, the performance of nonlinear approximation using activation functions can be improved. The scale and location parameters in each hidden layer can improve the performance of the deep neural network by determining parameters that minimize the loss function value through the learning process using the primary differential coefficient of the loss function for the parameters in the backpropagation. Through MNIST classification problems and XOR problems, parametric activation functions have been found to have superior performance over existing activation functions.

• Communications of the Korean Mathematical Society
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• 제32권1호
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• pp.75-84
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• 2017

In recent years, several interesting families of generating functions for various classes of hypergeometric functions were investigated systematically. In the present paper, we introduce a new family of extended Wright type hypergeometric function and obtain several classes of generating relations for this extended Wright type hypergeometric function.

• Communications of the Korean Mathematical Society
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• 제37권4호
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• pp.995-1007
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• 2022

In this article, we initiate subclasses of functions with boundary and radius rotations that are related to limaçon domains and examine some of their geometric properties. Radius results associated with functions in these classes and their linear combination are studied. Furthermore, the growth rate of coefficients, arc length and coefficient estimates are derived for these novel classes. Overall, some useful consequences of our findings are also illustrated.