• The Pure and Applied Mathematics
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• v.25 no.1
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• pp.1-5
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• 2018

It is proved that 'maximum' is actually attained in the following risk measure representation $${\rho}_m(X)={max \atop Q{\in}Q_m}E_Q[-X]$$.

• Journal of the Korean Mathematical Society
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• v.44 no.2
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• pp.487-498
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• 2007

In this paper, we obtain important combinatorial identities of generalized harmonic numbers using symmetric polynomials. We also obtain the matrix representation for the generalized harmonic numbers whose inverse matrix can be computed recursively.

• Journal for History of Mathematics
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• v.20 no.4
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• pp.153-174
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• 2007

The concept of Function is not just a single concept but an integrated concept that includes various mathematic topics such as arithmetics, geometry and so on. Therefore, the concept of function is the basic principal underlying mathematics. Moreover, we should think of function as conceptual expedient for understanding the phenomena in the variously changing real world. Therefore in this article, I would like to consider the concept of an integrated function through historical investigation. Especially, from the middle ages to the 19th century, representation which related to the function has been evolved, and therefore, I will consider function as an integrated concept through changing the concept of function.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.8
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• pp.1901-1906
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• 1995

The frequency response functions of systems incorporating a non-linear cubic stiffness subject to sinusoidal excitation are derived using the Volterra series and the convergence characteristics investigated. It is shown that the series representation of the frequency response functions converges only when the sinewave input amplitude is within a certain range. Within the range of convergence the frequency response function based on the Volterra series approaches the analytical one as more higher order frequency response function terms are included. Proposed is a criterion for the studies systems to predict approximately the range of sinewave input amplitude for which the series representation of the frequency response functions converges.

• Journal of applied mathematics & informatics
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• v.40 no.1_2
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• pp.205-213
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• 2022

In this paper we give a simple and direct proof of an Euler integral representation for a special class of _q+1F_q,k k-hypergeometric functions for q ≥ 2. The values of certain ₃F_2,k and ₄F_3,k functions at $x=\frac{1}{k}$, some of which can be derived using other methods. We may conclude that for k = 1 the results are reduced to [3].

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.499-503
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• 2009

Y. R$\acute{e}$ball$\acute{e}$ [11] discussed the representation of necessity measure through the Choquet integral criterian. He also consider a decision maker who ranks necessity measures related with Choquet integral representation. In this paper, we consider a decision maker have an "ambiguity"(say, interval-valued) necessity measure according to their Choquet's expected utility. Furthermore, we prove two theorems which are weak Choquet integral representation of preferences with a monotone set function for interval-valued necessity measures and strong Choquet integral representation of preferences with an interval-valued utility function for necessity measures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5464-5484
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• 2016

Few samples face recognition has become a highly challenging task due to the limitation of available labeled samples. As two popular paradigms in face image representation, sparse component analysis is highly robust while parts-based paradigm is particularly flexible. In this paper, we propose a probabilistic generative model to incorporate the strengths of the two paradigms for face representation. This model finds a common spatial partition for given images and simultaneously learns a sparse component analysis model for each part of the partition. The two procedures are built into a probabilistic generative model. Then we derive the score function (i.e. feature mapping) from the generative score space. A similarity measure is defined over the derived score function for few samples face recognition. This model is driven by data and specifically good at representing face images. The derived generative score function and similarity measure encode information hidden in the data distribution. To validate the effectiveness of the proposed method, we perform few samples face recognition on two face datasets. The results show its advantages.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.817-821
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• 2001

In this paper, a new learning methodology for kernel methods that results in a sparse representation of kernel space from the training patterns for classification problems is suggested. Among the traditional algorithms of linear discriminant function, this paper shows that the relaxation procedure can obtain the maximum margin separating hyperplane of linearly separable pattern classification problem as SVM(Support Vector Machine) classifier does. The original relaxation method gives only the necessary condition of SV patterns. We suggest the sufficient condition to identify the SV patterns in the learning epoches. For sequential learning of kernel methods, extended SVM and kernel discriminant function are defined. Systematic derivation of learning algorithm is introduced. Experiment results show the new methods have the higher or equivalent performance compared to the conventional approach.

• Nonlinear Functional Analysis and Applications
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• v.29 no.1
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• pp.99-111
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• 2024

In this paper, a new seven-parameter Mittag-Leffler function of a single complex variable is proposed as a generalization of the standard Mittag-Leffler function, certain generalizations of Mittag-Leffler function, hypergeometric function and confluent hypergeometric function. Certain essential analytic properties are mainly discussed, such as radius of convergence, order, type, differentiation, Mellin-Barnes integral representation and Euler transform in the complex plane. Its relation to Fox-Wright function and H-function is also developed.

• School Mathematics
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• v.11 no.1
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• pp.131-145
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• 2009

This research was designed to investigate the possibility to teach function concept and graph representation of functions in explicit manner toward at elementary level. Eight class-hours instruction was given to four Grade 5(age 11) students, and dynamic geometry software GSP was partially used in the class. Results indicate that the students could conceptualize the function relation, interpret linear function graphs, recognize the meaning of their slopes, and discuss the relationships among linear graphs and real life situation. Results also indicate that GSP helped students to recognize the relation between dots and the linear graph clearly and that GSP-line graph did decisive role for children to understand the meaning of graph representation of function.