• 제목/요약/키워드: Autoregressive Process

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VBR MPEG 비디오 추적을 위한 임계치 자회귀 모델 (Threshold Autoregressive Models for VBR MPEG Video Traces)

  • 오창윤;배상현
    • 한국컴퓨터정보학회논문지
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    • 제4권4호
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    • pp.101-112
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    • 1999
  • NPEG은 ISO 산하의 표준화 위원회에서 동영상 압축 기술의 필요에 의해 표준화된 동영상 압축 기술로 통신상에서 더 높은 비트율의 고화질 동화상 실현의 요구에 의해 1995년에 MPEG 2가 개발되었다. 본 논문에서는 VBR MPEG의 코드화된 완전한 동화상 통신을 위해 비선형 시계열 방식으로 효율적이고도 정확한 TAR모델 설계 알고리즘을 제안하며 실질적인 동영상 비디오 추적에 대한 통계적 특성을 보여주는 시뮬레이션 결과를 제시하고자 한다.

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Doubly penalized kernel method for heteroscedastic autoregressive datay

  • Cho, Dae-Hyeon;Shim, Joo-Yong;Seok, Kyung-Ha
    • Journal of the Korean Data and Information Science Society
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    • 제21권1호
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    • pp.155-162
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    • 2010
  • In this paper we propose a doubly penalized kernel method which estimates both the mean function and the variance function simultaneously by kernel machines for heteroscedastic autoregressive data. We also present the model selection method which employs the cross validation techniques for choosing the hyper-parameters which aect the performance of proposed method. Simulated examples are provided to indicate the usefulness of proposed method for the estimation of mean and variance functions.

PERFORMANCE OF THE AUTOREGRESSIVE METHOD IN LONG-TERM PREDICTION OF SUNSPOT NUMBER

  • Chae, Jongchul;Kim, Yeon Han
    • 천문학회지
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    • 제50권2호
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    • pp.21-27
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    • 2017
  • The autoregressive method provides a univariate procedure to predict the future sunspot number (SSN) based on past record. The strength of this method lies in the possibility that from past data it yields the SSN in the future as a function of time. On the other hand, its major limitation comes from the intrinsic complexity of solar magnetic activity that may deviate from the linear stationary process assumption that is the basis of the autoregressive model. By analyzing the residual errors produced by the method, we have obtained the following conclusions: (1) the optimal duration of the past time for the forecast is found to be 8.5 years; (2) the standard error increases with prediction horizon and the errors are mostly systematic ones resulting from the incompleteness of the autoregressive model; (3) there is a tendency that the predicted value is underestimated in the activity rising phase, while it is overestimated in the declining phase; (5) the model prediction of a new Solar Cycle is fairly good when it is similar to the previous one, but is bad when the new cycle is much different from the previous one; (6) a reasonably good prediction of a new cycle can be made using the AR model 1.5 years after the start of the cycle. In addition, we predict the next cycle (Solar Cycle 25) will reach the peak in 2024 at the activity level similar to the current cycle.

2차원 GFRC절삭에서 AR모델링에 관한 연구 (Autoregressive Modeling in Orthogonal Cutting of Glass Fiber Reinforced Composites)

  • Gi Heung Choi
    • 한국안전학회지
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    • 제16권1호
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    • pp.88-93
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    • 2001
  • 본 연구에서는 복합소재인 GFRP(Glass Fiber Reinforced Polyester)의 2차원 절삭공정에서 절삭 메커니즘과 소재의 신뢰도 및 안전성과 밀접한 관련이 있는 표면정도를 중심으로 한 공정의 특성화를 시도하고, 주파수 분석에 관하여도 논의한다. 구체적으로는, 공정중 발생하는 절삭력 신호를 AR(Autoregressive) 모델링하여 해석에 사용한다. 특히, 특징추출과정을 통해 AR계수로 이루어진 패턴벡터 중 다양한 절삭 메카니즘에 민감한 계수만 선택할 수 있다. 이들 계수와 절삭 메커니즘과의 실험적 관계를 설정함으로써 섬유경사각(Fiber orientation angle), 절삭 변수 그리고 공구형상이 절삭 메커니즘에 미치는 영향을 평가하였다.

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LDV의 난류 스펙트럼 추정치 평가 (Assessment of Turbulent Spectral Estimators in LDV)

  • 이도환;성형진
    • 대한기계학회논문집
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    • 제16권9호
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    • pp.1788-1795
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    • 1992
  • 본 연구에서는 상술한 특성을 갖는 유동자에 대하여 신뢰성이 보장된 스펙트 럼 추정법의 모색과 화립을 위해 의사 난류신호(turbulent-like signal)를 자기회기 모형(autoregressive model:AR model)으로 생성하고 추출간격이 유동장에 영향을 받는 비주기적 확률과정을 수치적으로 모사한다. 이 비주기적 실현 신호로 부터 현재 가 장 많이 사용되고 있는 Roberts와 Gaster의 직접 변화법과 추출 및 유지신호의 피리오 도그램(periodogram)법에 대해 데이터 밀도와 난류강도의 다양한 변화에 따른 속도편 의의 영향 등을 살펴보는데 목적을 둔다.

Preliminary Identification of Branching-Heteroscedasticity for Tree-Indexed Autoregressive Processes

  • Hwang, S.Y.;Choi, M.S.
    • Communications for Statistical Applications and Methods
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    • 제18권6호
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    • pp.809-816
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    • 2011
  • A tree-indexed autoregressive(AR) process is a time series defined on a tree which is generated by a branching process and/or a deterministic splitting mechanism. This short article is concerned with conditional heteroscedastic structure of the tree-indexed AR models. It has been usual in the literature to analyze conditional mean structure (rather than conditional variance) of tree-indexed AR models. This article pursues to identify quadratic conditional heteroscedasticity inherent in various tree-indexed AR models in a unified way, and thus providing some perspectives to the future works in this area. The identical conditional variance of sisters sharing the same mother will be referred to as the branching heteroscedasticity(BH, for short). A quasilikelihood but preliminary estimation of the quadratic BH is discussed and relevant limit distributions are derived.

선형예측을 이용한 EMG 신호처리에 관한 연구 (A Study on EMG Signal Processing Using Linear Prediction)

  • 박상희
    • 대한전자공학회논문지
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    • 제24권2호
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    • pp.280-291
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    • 1987
  • In this paper, the linear autoregressive model of EMG signal for four basic arm functions was presented and parameters for each function were estimated. The signal identification was carried out using function discrimination algorithm. It was validated that EMG signal was a widesense stationary process and the linear autoregressive model of EMG signal was constructed through approximating it to Gaussian process. It was confined that Levinson-Durbin algoridthm is a more appropriate one than the recursive least square method for parameter estimation of the linear model. Optimal function discrimination was acquired when sampling frequency was 500Hz and two electrodes were attached to bicep and tricep muscle, respectively. Parameter values were independent of variance and the number of minimum data for function discrimination was 200. Bayesian discrimination method turned out to be a better one than parallel filtering method for functional discrimination recognition.

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