• Title/Summary/Keyword: Periodic

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EXISTENCE OF FUNCTIONAL DIFFERENTIAL EQUATIONS WITH STEPANOV FORCING TERMS.

  • Lee, Hyun Mork
    • Journal of the Chungcheong Mathematical Society
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    • v.33 no.3
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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.

ON THE MINKOWSKI UNITS OF 2-PERIODIC KNOTS

  • Lee, Sang-Youl
    • Bulletin of the Korean Mathematical Society
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    • v.38 no.3
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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.

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ALMOST PERIODIC SOLUTIONS OF LINEAR DIFFERENCE SYSTEMS

  • Im, Dong Man;Goo, Yoon Hoe
    • Journal of the Chungcheong Mathematical Society
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    • v.19 no.2
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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.

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Partial H-plane Filter with Periodic Structure (주기 구조를 이용한 Partial H-plane Filter)

  • Kim Dong-Jin;Chung Woo-Sung;Lee Jeong-Hae
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.17 no.8 s.111
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    • pp.746-752
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    • 2006
  • In this paper, a compact partial H-plane filter with periodic structure is proposed. Guided wavelength of periodic structure' is reduced by slow wave effect. Cross-section and length of partial H-plane filter with periodic structure are considerably reduced by 75% and 30%, respectively, as compared with conventional E-plane filter. In addition, spurious responses of the bandpass filter are improved. To design bandpass filter with periodic structure, we have analyzed a periodic structure of partial H-plane waveguide and derived equations of the periodic filter. Measured results are in good agreement with simulated results.

New Construction Method for Quaternary Aperiodic, Periodic, and Z-Complementary Sequence Sets

  • Zeng, Fanxin;Zeng, Xiaoping;Zhang, Zhenyu;Zeng, Xiangyong;Xuan, Guixin;Xiao, Lingna
    • Journal of Communications and Networks
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    • v.14 no.3
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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.

16-QAM Periodic Complementary Sequence Mates Based on Interleaving Technique and Quadriphase Periodic Complementary Sequence Mates

  • Zeng, Fanxin;Zeng, Xiaoping;Xiao, Lingna;Zhang, Zhenyu;Xuan, Guixin
    • Journal of Communications and Networks
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    • v.15 no.6
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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.

Outlier prediction in sensor network data using periodic pattern (주기 패턴을 이용한 센서 네트워크 데이터의 이상치 예측)

  • Kim, Hyung-Il
    • Journal of Sensor Science and Technology
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    • v.15 no.6
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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.