• 충청수학회지
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• 제33권3호
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• pp.351-363
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• 2020

We introduce a new concept of Stepanov weighted pseudo almost periodic functions of class r which have been established by recently in [20]. Furthermore, we study the uniqueness and existence of Stepanov weighted pseudo almost periodic mild solutions of partial neutral functional differential equations having the Stepanov pseudo almost periodic forcing terms on finite delay.

• 충청수학회지
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• 제20권4호
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• pp.449-455
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• 2007

We obtain a discrete version of a fundamental result by Yoshizawa related to the existence of almost periodic solutions of functional differential equations with finite delay.

• 대한수학회보
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• 제47권2호
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• pp.355-367
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• 2010

In this paper, the existence of periodic solutions is obtained for a kind of p-Laplacian systems by the minimax methods in critical point theory. Moreover, the existence of infinite periodic solutions is also obtained.

• 대한수학회보
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• 제38권3호
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• pp.475-486
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• 2001

In this paper we give a relationship among the Minkowski units, for all odd prime number including $\infty$, of 2-periodic knot is $S^3$, its factor knot, and the 2-component link consisting of the factor knot and the set of fixed points of the periodic action.

• 충청수학회지
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• 제19권2호
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• pp.153-158
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• 2006

In this paper, we present an elementary proof for the existence of almost periodic solutions of linear nonhomogeneous difference systems.

• 충청수학회지
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• 제23권2호
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• pp.401-409
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• 2010

We study the existence of periodic solutions of Volterra equations by using the limiting equations and contraction mappings.

• 한국전자파학회논문지
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• 제17권8호
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• pp.746-752
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• 2006

본 논문에서는 주기 구조를 이용한 소형화된 partial H-plane필터를 제안하였다. 주기 구조의 관내 파장은 저속파의 영향으로 인해 그 크기가 줄어든다. 주기 구조를 이용한 partial H-plane 필터는 일반적인 E-plane 필터보다 단면적과 길이가 각각 75%, 30% 축소되었다. 또한 대역 통과 필터의 스퓨리어스 응답 특성이 향상되었다. 주기 구조를 이용한 대역 통과 필터를 설계하기 위해 partial H-plane 도파로의 주기 구조가 해석되었고, 설계식이 유도되었다. 측정된 결과는 시뮬레이션 결과와 잘 일치함을 확인할 수 있었다.

• Journal of Communications and Networks
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• 제14권3호
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• pp.230-236
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• 2012

Based on the known binary sequence sets and Gray mapping, a new method for constructing quaternary sequence sets is presented and the resulting sequence sets' properties are investigated. As three direct applications of the proposed method, when we choose the binary aperiodic, periodic, and Z-complementary sequence sets as the known binary sequence sets, the resultant quaternary sequence sets are the quaternary aperiodic, periodic, and Z-complementary sequence sets, respectively. In comparison with themethod proposed by Jang et al., the new method can cope with either both the aperiodic and periodic cases or both even and odd lengths of sub-sequences, whereas the former is only fit for the periodic case with even length of sub-sequences. As a consequence, by both our and Jang et al.'s methods, an arbitrary binary aperiodic, periodic, or Z-complementary sequence set can be transformed into a quaternary one no matter its length of sub-sequences is odd or even. Finally, a table on the existing quaternary periodic complementary sequence sets is given as well.

• Journal of Communications and Networks
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• 제15권6호
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• pp.581-588
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• 2013

Based on an interleaving technique and quadriphase periodic complementary sequence (CS) mates, this paper presents a method for constructing a family of 16-quadrature amplitude modulation (QAM) periodic CS mates. The resulting mates arise from the conversion of quadriphase periodic CS mates, and the period of the former is twice as long as that of the latter. In addition, based on the existing binary periodic CS mates, a table on the existence of the proposed 16-QAM periodic CS mates is given. Furthermore, the proposed method can also transform a mutually orthogonal (MO) quadriphase CS set into an MO 16-QAM CS set. Finally, three examples are given to demonstrate the validity of the proposed method.

• 센서학회지
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• 제15권6호
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• pp.433-441
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• 2006

Because of the low power and low rate of a sensor network, outlier is frequently occurred in the time series data of sensor network. In this paper, we suggest periodic pattern analysis that is applied to the time series data of sensor network and predict outlier that exist in the time series data of sensor network. A periodic pattern is minimum period of time in which trend of values in data is appeared continuous and repeated. In this paper, a quantization and smoothing is applied to the time series data in order to analyze the periodic pattern and the fluctuation of each adjacent value in the smoothed data is measured to be modified to a simple data. Then, the periodic pattern is abstracted from the modified simple data, and the time series data is restructured according to the periods to produce periodic pattern data. In the experiment, the machine learning is applied to the periodic pattern data to predict outlier to see the results. The characteristics of analysis of the periodic pattern in this paper is not analyzing the periods according to the size of value of data but to analyze time periods according to the fluctuation of the value of data. Therefore analysis of periodic pattern is robust to outlier. Also it is possible to express values of time attribute as values in time period by restructuring the time series data into periodic pattern. Thus, it is possible to use time attribute even in the general machine learning algorithm in which the time series data is not possible to be learned.