• Title/Summary/Keyword: Autocorrelation method

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Temperature Effect on the Configurational Properties of an n-Decane Chain in Solution

  • Oh, In-Joon;Ree, Tai-Kyue
    • Bulletin of the Korean Chemical Society
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    • v.5 no.4
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    • pp.162-167
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    • 1984
  • Equilibrium and dynamical behaviors of an n-alkane poymer (decane) in solution have been investigated by a molecuar dynamics simulation method. The polymer is assumed to be a chain of elements $(CH_2)$ interconnected by bonds having a fixed bond length and bond angle, but esch bond of the polymer is allowed to execute hindered internal rotation. The calculation explicitly considers the molecular naturer of solvent by including the intermolecular interactions between slovent-solvent molecules and chain element-solvent molecule. We present the results of calculations on (1) equilibrium properties (the solvent molecule-chain element pair correlation function, chain element-chain element pair correlation function, the mean square end-to-end distance and the mean square radius of gyration of the polymer) and (2) dynamic properties (four different autocorrelation functions, namely, the autocorrelation functions for the end-to-end distance and the radius of gyration, and the velocity autocorrelation functions for the center of mass and the end point of the chain). We found that the physical properties of the polymer chain depends sensitively on temperature. Comparison of the present work with other authors' results is also presented.

Estimating Three-Dimensional Scattering Centers of a Target Using the 3D MEMP Method in Radar Target Recognition (레이다 표적 인식에서 3D MEMP 기법을 이용한 표적의 3차원 산란점 예측)

  • Shin, Seung-Yong;Myung, Noh-Hoon
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.19 no.2
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    • pp.130-137
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    • 2008
  • This paper presents high resolution techniques of three-dimensional(3D) scattering center extraction for a radar backscattered signal in radar target recognition. We propose a 3D pairing procedure, a new approach to estimate 3D scattering centers. This pairing procedure is more accurate and robust than the general criterion. 3D MEMP(Matrix Enhancement and Matrix Pencil) with the 3D pairing procedure first creates an autocorrelation matrix from radar backscattered field data samples. A matrix pencil method is then used to extract 3D scattering centers from the principal eigenvectors of the autocorrelation matrix. An autocorrelation matrix is constructed by the MSSP(modified spatial smoothing preprocessing) method. The observation matrix required for estimation of 3D scattering center locations is built using the sparse scanning order conception. In order to demonstrate the performance of the proposed technique, we use backscattered field data generated by ideal point scatterers.

A Study on a Statistical Modeling of 3-Dimensional MPEG Data and Smoothing Method by a Periodic Mean Value (3차원 동영상 데이터의 통계적 모델링과 주기적 평균값에 의한 Smoothing 방법에 관한 연구)

  • Kim, Duck-Sung;Kim, Tae-Hyung;Rhee, Byung-Ho
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.6
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    • pp.87-95
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    • 1999
  • We propose a simulation model of 3-dimensional MPEG data over Asynchronous transfer Mode(ATM) networks. The model is based on a slice level and is named to Projected Vector Autoregressive(PVAR) model. The PVAR model is modeled using the Autoregressive(AR) model in order to meet the autocorrelation condition and fit the histogram, and maps real data by a projection function. For the projection function, we use the Cumulative Distribution Probability Function (CDPF), and the procedure is performed at each slice level. Our proposed model shows good performance in meeting the autocorrelation condition and fitting the histogram, and is found important in analyzing the performance of networks. In addiotion, we apply a smoothing method by which a periodic mean value. In general. the Quality of Service(QoS) depends on the Cell Loss Rate(CLR), which is related to the cell loss and a maximum delay in a buffer. Hence the proposed smoothing method can be used to improve the QoS.

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Identifying Spatial Distribution Pattern of Water Quality in Masan Bay Using Spatial Autocorrelation Index and Pearson's r (공간자기상관 지수와 Pearson 상관계수를 이용한 마산만 수질의 공간분포 패턴 규명)

  • Choi, Hyun-Woo;Park, Jae-Moon;Kim, Hyun-Wook;Kim, Young-Ok
    • Ocean and Polar Research
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    • v.29 no.4
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    • pp.391-400
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    • 2007
  • To identify the spatial distribution pattern of water quality in Masan Bay, Pearson's correlation as a common statistic method and Moran's I as a spatial autocorrelation statistics were applied to the hydrological data seasonally collected from Masan Bay for two years ($2004{\sim}2005$). Spatial distribution of salinity, DO and silicate among the hydrological parameters clustered strongly while chlorophyll a distribution displayed a weak clustering. When the similarity matrix of Moran's I was compared with correlation matrix of Pearson's r, only the relationships of temperature vs. salinity, temperature vs. silicate and silicate vs. total inorganic nitrogen showed significant correlation and similarity of spatial clustered pattern. Considering Pearson's correlation and the spatial autocorrelation results, water quality distribution patterns of Masan Bay were conceptually simplified into four types. Based on the simplified types, Moran's I and Pearson's r were compared respectively with spatial distribution maps on salinity and silicate with a strong clustered pattern, and with chlorophyll a having no clustered pattern. According to these test results, spatial distribution of the water quality in Masan Bay could be summed up in four patterns. This summation should be developed as spatial index to be linked with pollutant and ecological indicators for coastal health assessment.

Nonlinear Analog of Autocorrelation Function (자기상관함수의 비선형 유추 해석)

  • Kim, Hyeong-Su;Yun, Yong-Nam
    • Journal of Korea Water Resources Association
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    • v.32 no.6
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    • pp.731-740
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    • 1999
  • Autocorrelation function is widely used as a tool measuring linear dependence of hydrologic time series. However, it may not be appropriate for choosing decorrelation time or delay time ${\tau}_d$ which is essential in nonlinear dynamics domain and the mutual information have recommended for measuring nonlinear dependence of time series. Furthermore, some researchers have suggested that one should not choose a fixed delay time ${\tau}_d$ but, rather, one should choose an appropriate value for the delay time window ${\tau}_d={\tau}(m-1)$, which is the total time spanned by the components of each embedded point for the analysis of chaotic dynamics. Unfortunately, the delay time window cannot be estimated using the autocorrelation function or the mutual information. Basically, the delay time window is the optimal time for independence of time series and the delay time is the first locally optimal time. In this study, we estimate general dependence of hydrologic time series using the C-C method which can estimate both the delay time and the delay time window and the results may give us whether hydrologic time series depends on its linear or nonlinear characteristics which are very important for modeling and forecasting of underlying system.

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Engineered Surface Characterization by Space Series Function (공간 계열 함수를 이용한 가공표면의 특성 연구)

  • 홍민성
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.04a
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    • pp.521-525
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    • 1996
  • An attempt is made to characterize and synthesize engineered surfaces. The proposed method is not only an analytical tool to characterize but alsoto generate/synthesize three-dimensional surfaces. The developed method expresses important engineered surface characteristics such as the autocorrelation or pwoer spectrum density functions in terms of the two-dimensional autoregressive coefficients.

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An Experimental Method of Ship Wave Analysis (선파분석(船波分析)의 일실험적방법(一實驗的方法))

  • Hun-Chol,Kim;F.C.,Michelsen
    • Bulletin of the Society of Naval Architects of Korea
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    • v.5 no.2
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    • pp.35-44
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    • 1968
  • The longitudinal cut method of experimental ship wave analysis, originally developed by J.N. Newman, is presented and various plausible sources of error are discussed. A further use of autocorrelation function and crosscorrelation function when two wave systems are superposed is indicated.

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Recognition of PRI modulation types of radar signals using the autocorrelation (자기상관관계를 이용한 레이더 신호의 PRI 변조형태 인식 기법)

  • Ryoo Young-Jin;Kim Whan-Woo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.3 s.309
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    • pp.61-67
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    • 2006
  • In electronic support systems, the analysis of PRI modulation characteristics for radar signals has attracted much interest because of the problem of the identification ambiguity in dense electronic warfare signal environments. A new method of recognizing the PRI modulation types of radar pulse signals is proposed for electronic support. The proposed method recognizes the PRI modulation types using the classifiers which are based on the property of the linear autocorrelation of the PRI sequences for each PRI modulation type. In addition, the proposed method estimates the PRI modulation period for the PRI modulation types with the periodicity. Simulation results are presented to show the performance of the proposed method.

Symbol Synchronization of OFDM Systems using Signs of Preamble Signals (훈련신호의 부호를 사용한 OFDM 시스템의 심볼동기)

  • 황진권
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.5A
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    • pp.502-513
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    • 2004
  • This paper proposes a symbol synchronization method in the IEEE 802.11a wireless OPDM system, which uses only signs of the in-phase and the quadrature signals in the short preamble. The short preamble is sampled with 2 tines of Nyquist sampling rate and both of the autocorrelation and the cross-relation are used in the proposed method. This method has some advantages that the ACG (Automatic Gain Control) can be processed concurrently during the short preamble and its implementation is not much complicated. The proposed symbol synchronization method is verified through simulations on frequency offset, multi-path and white Gaussian noise.

A Comparative Study of the GPAC Method and the 3-pattern Method for Identifying ARMA Processes

  • Chul Eung KIM;ByoungSeon CHOI
    • Communications for Statistical Applications and Methods
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    • v.3 no.3
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    • pp.47-58
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    • 1996
  • The generalized partial autocorrelation (GPAC) method of Woodward and Gray (1981) and the 3-pattern method of Choi (1991) have been used for identifying ARMA processes. The methods are based on the extended Yule-Walker equations. The purpose of this paper is to show the 3-pattern method is superior to the GPAC method through theoretical analysis and computer simulations.

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