• Title/Summary/Keyword: autocovariance

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A Probabilistic Interpretation of the KL Spectrum

  • Seongbaek Yi;Park, Byoung-Seon
    • Journal of the Korean Statistical Society
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    • v.29 no.1
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    • pp.1-8
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    • 2000
  • A spectrum minimizing the frequency-domain Kullback-Leibler information number has been proposed and used to modify a spectrum estimate. Some numerical examples have illustrated the KL spectrum estimate is superior to the initial estimate, i.e., the autocovariances obtained by the inverse Fourier transformation of the KL spectrum estimate are closer to the sample autocovariances of the given observations than those of the initial spectrum estimate. Also, it has been shown that a Gaussian autoregressive process associated with the KL spectrum is the closest in the timedomain Kullback-Leibler sense to a Gaussian white noise process subject to given autocovariance constraints. In this paper a corresponding conditional probability theorem is presented, which gives another rationale to the KL spectrum.

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A Study on the Improvement of the Batch-means Method in Simulation Analysis (모의실험 분석중 구간평균기법의 개선을 위한 연구)

  • 천영수
    • Journal of the Korea Society for Simulation
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    • v.5 no.2
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    • pp.59-72
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    • 1996
  • The purpose of this study is to make an improvement to the batch-means method, which is a procedure to construct a confidence interval(c.i.) for the steady-state process mean of a stationary simulation output process. In the batch-means method, the data in the output process are grouped into batches. The sequence of means of the data included in individual batches is called a batch-menas process and can be treated as an independently and identically distributed set of variables if each batch includes sufficiently large number of observations. The traditional batch-means method, therefore, uses a batch size as large as possible in order to. destroy the autocovariance remaining in the batch-means process. The c.i. prodedure developed and empirically tested in this study uses a small batch size which can be well fitted by a simple ARMA model, and then utilizes the dependence structure in the fitted model to correct for bias in the variance estimator of the sample mean.

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Assessment of speckle image through particle size and image sharpness

  • Qian, Boxing;Liang, Jin;Gong, Chunyuan
    • Smart Structures and Systems
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    • v.24 no.5
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    • pp.659-668
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    • 2019
  • In digital image correlation, speckle image is closely related to the measurement accuracy. A practical global evaluation criterion for speckle image is presented. Firstly, based on the essential factors of the texture image, both the average particle size and image sharpness are used for the assessment of speckle image. The former is calculated by a simplified auto-covariance function and Gaussian fitting, and the latter by focusing function. Secondly, the computation of the average particle size and image sharpness is verified by numerical simulation. The influence of these two evaluation parameters on mean deviation and standard deviation is discussed. Then, a physical model from speckle projection to image acquisition is established. The two evaluation parameters can be mapped to the physical devices, which demonstrate that the proposed evaluation method is reasonable. Finally, the engineering application of the evaluation method is pointed out.

A Newton-Raphson Solution for MA Parameters of Mixed Autoregressive Moving-Average Process

  • Park, B. S.
    • Journal of the Korean Statistical Society
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    • v.16 no.1
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    • pp.1-9
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    • 1987
  • Recently a new form of the extended Yule-Walker equations for a mixed autoregressive moving-average process of orders p and q has been proposed. It can be used to obtain p+q+1 parameter values from the first p+q+1 autocovariance terms. The autoregressive part of the equations is linear and can be easily solved. In contrast the moving-average part is composed of nonlinear simultaneous equations. Thus some iterative algorithms are necessary to solve them. The iterative algorithm presented by Choi(1986) is very simple but its convergence has not been proved yet. In this paper a Newton-Raphson solution for the moving-average parameters is presented and its convergence is shown. Also numerical example illustrate the performance of the algorithm.

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Gradient On-Off Beamforming Algorithm Based On Eigen-Space Method For a Smart Antenna In IS-2000 1X Signal Environment (IS-2000 1X 신호 환경하에서의 고유공간 방법에 근간한 그래디언트 온-오프 빔평성 알고리즘)

  • 이정자;이원철;최승원
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.10C
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    • pp.949-957
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    • 2003
  • This paper presents a gradient ON-OFF algorithm of which the performance is very robust even when the angle spread increases in the mobile communication environments. The proposed method getting the diversity gain by utilizing the primary and secondary eigenvector, which corresponds to the largest and the second largest eigenvalue of the autocovariance matrix of the received signal vector, outperforms the method which just utilizes one eigenvector. By applying the proposed method to IS-2000 1X signal environments, it is observed that the proposed method shows excellent performance compared to a typical beamforming method using just one eigenvector, which considerably degrades the receiving performance as the angle spread increases.

A development of multisite hourly rainfall simulation technique based on neyman-scott rectangular pulse model (Neyman-Scott Rectangular Pulse 모형 기반의 다지점 강수모의 기법 개발)

  • Moon, Jangwon;Kim, Janggyeong;Moon, Youngil;Kwon, Hyunhan
    • Journal of Korea Water Resources Association
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    • v.49 no.11
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    • pp.913-922
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    • 2016
  • A long-term precipitation record is typically required for establishing the reliable water resources plan in the watershed. However, the observations in the hourly precipitation data are not always consistent and there are missing values within the time series. This study aims to develop a hourly rainfall simulator for extending rainfall data, based on the well-known Neyman-Scott Rectangular Pulse Model (NSRPM). Moreover, this study further suggests a multisite hourly rainfall simulator to better reproduce areal rainfalls for the watershed. The proposed model was validated with a network of five weather stations in the Uee-stream watershed in Seoul. The proposed model appeared a reasonable result in terms of reproducing most of the statistics (i.e. mean, variance and lag-1 autocovariance) of the rainfall time series at various aggregation levels and the spatial coherence over the weather stations.

Deisgn of adaptive array antenna for tracking the source of maximum power and its application to CDMA mobile communication (최대 고유치 문제의 해를 이용한 적응 안테나 어레이와 CDMA 이동통신에의 응용)

  • 오정호;윤동운;최승원
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.11
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    • pp.2594-2603
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    • 1997
  • A novel method of adaptive beam forming is presented in this paper. The proposed technique provides for a suboptimal beam pattern that increases the Signal to Noise/Interference Ratio (SNR/SIR), thus, eventually increases the capacity of the communication channel, under an assumption that the desired signal is dominant compared to each component of interferences at the receiver, which is precoditionally achieved in Code Division Multiple Access (CDMA) mobile communications by the chip correlator. The main advantages of the new technique are:(1)The procedure requires neither reference signals nor training period, (2)The signal interchoerency does not affect the performance or complexity of the entire procedure, (3)The number of antennas does not have to be greater than that of the signals of distinct arrival angles, (4)The entire procedure is iterative such that a new suboptimal beam pattern be generated upon the arrival of each new data of which the arrival angle keeps changing due tot he mobility of the signal source, (5)The total amount of computation is tremendously reduced compared to that of most conventional beam forming techniques such that the suboptimal beam pattern be produced at vevery snapshot on a real-time basis. The total computational load for generating a new set of weitht including the update of an N-by-N(N is the number of antenna elements) autocovariance matrix is $0(3N^2 + 12N)$. It can further be reduced down to O(11N) by approximating the matrix with the instantaneous signal vector.

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