• Title, Summary, Keyword: ARMA

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A Covariance Type ARMA Fast Transversal Filter (공분산형 ARMA 고속 Transversal 필터에 관한 연구)

  • Lee, Chul-Heui;Jang, Young-Soo
    • The Journal of the Acoustical Society of Korea
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    • v.11 no.1
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    • pp.67-79
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    • 1992
  • For effective on-line ARMA parameter estimation, a covariance type ARMA fast transversal filter (FTF) algorithm is presented. The proposed algorithm is a covariance type implementation of ELS(Extended Least Squares) estimator and it is a fast time update recursion which is based on the fact that the correlation matrix of ARMA model satisfies the shift invariance property in each sub-block. The geometric approach is used in the derivation of the proposed algorithm. It takes small computational burden of 13N+37 MADPR(Multiplication And Division Per Recursion). Also, AR and MA orders can be independetly and arbitrarily specified.

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Sufficient Conditions for Stationarity of Smooth Transition ARMA/GARCH Models

  • Lee, Oe-Sook
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.1
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    • pp.237-245
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    • 2007
  • Nonlinear asymmetric time series models have the growing interest in econometrics and finance. Threshold model is one of the successful asymmetric model. We consider a smooth transition ARMA model which converges a.s. to a threshold ARMA model and show that the smooth transition ARMA model admits a stationary measure, provided a suitable condition on the coefficients of the autoregressive parts of the different regimes is satisfied. Stationarity of a smooth transition GARCH model is also obtained.

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A Synthetic Generation of Streamflows by ARMA(1, 1) Multiseason Model (ARMA(1, 1) 다계절모형에 의한 하천유량의 모의발생)

  • 윤용남;전시영
    • Water for future
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    • v.18 no.1
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    • pp.75-83
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    • 1985
  • The applicability of ARMA(1, 1) multiseason model, which is in the beginning stage of active researches in the field of synthetic generation is evaluated with the streamflow data at the Nakdong stage gauging station on the main stem of the Nakdong River. The method of parameter estimation for the modelis reviewed and the statistical analysis of the generated seasonal streamflows such as corrlogram analysis and the computation of moments is made. The results obtained by ARMA(1, 1) multiseason model are compared with the historical streamflow data and also with those by two other multiseason models, namely, Thomas-Fiering model and Matalas AR(1) multiseason model. The seasonal streamflows grnerated by three multiseason models were annually summed up to form respective annual flow series whose statistics were compared with those of the annual flow series generated by three annual models, namely, AR(1), Matalas AR(1), and ARMA(1, 1) annual models. The possibility of ARMA(1, 1) multiseason model for the simultaneous generation of seasonal and annual streamflows is also evaluated.

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ARMA System identification Using GTLS method and Recursive GTLS Algorithm (GTLS의 ARMA시트템식별에의 적용 및 적응 GTLS 알고리듬에 관한 연구)

  • Kim, Jae-In;Kim, Jin-Young;Rhee, Tae-Won
    • The Journal of the Acoustical Society of Korea
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    • v.14 no.3
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    • pp.37-48
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    • 1995
  • This paper presents an sstimation of ARMA coefficients of noisy ARMA system using generalized total least square (GTLS) method. GTLS problem for ARMA system is defined as minimizing the errors between the noisy output vectors and estimated noisy-free output. The GTLS problem is solved in closed form by eigen-problem and the perturbation analysis of GTLS is presented. Also its recursive solution (recursive GTLS) is proposed using the power method and the covariance formula of the projected output error vector into the input vector space. The simulation results show that GTLS ARMA coefficients estimator is an unbiased estimator and that recursive GTLS achieves fast convergence.

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Predictive Resource Allocation Scheme based on ARMA model in Mobile Cellular Networks (ARMA 모델을 이용한 모바일 셀룰러망의 예측자원 할당기법)

  • Lee, Jin-Yi
    • Journal of Advanced Navigation Technology
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    • v.11 no.3
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    • pp.252-258
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    • 2007
  • There has been a lot of research done in scheme guaranteeing user's mobility and effective resources management to satisfy the requested by users in the wireless/mobile networks. In this paper, we propose a predictive resource allocation scheme based on ARMA(Auto Regressive Moving Average) prediction model to meet QoS requirements(handoff dropping rate) for guaranteeing users' mobility. The proposed scheme predicts the demanded amount of resource in the future time by ARMA time series prediction model, and then reserves it. The ARMA model can be used to take into account the correlation of future handoff resource demands with present and past handoff demands for provision of targeted handoff dropping rate. Simulation results show that the proposed scheme outperforms the existing RCS(Reserved channel scheme) in terms of handoff connection dropping rate and resource utilization.

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Spectral Analysis of the ECG Using the Improved ARMA FTF Algorithm (개선된 ARMA FTF 알고리즘을 이용한 ECG 신호의 스펙트럼 해석)

  • Nam, Hyeon-Do;An, Dong-Jun;Lee, Cheol-Hui
    • Journal of Biomedical Engineering Research
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    • v.15 no.4
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    • pp.395-400
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    • 1994
  • High resolution spectral analysis is essential for ECG anaysis. The fast Fourier transform has been widely used for frequency analysis of ECG signals but this procedure provides poor resolution when the data record is short and shows Gibb's phenomena. The ARMA FTF (Fast Transversal Filter) algorithm is used for high resolution spectral analysis. The reason of unsalability of this algorithm is investigated and the method for improving the numerical stability is proposed. The proposed algorithm is applied to spectral analysis of the ECG. Since this result has less variations than the FFT based results, it can be used for the computerized diagonosis of the ECG.

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ELS FTF algorithm fot ARMA spectral estimation (ARMA스펙트럼 추정을 위한 ELS FTF 알고리즘)

  • 이철희;장영수;남현도;양홍석
    • 제어로봇시스템학회:학술대회논문집
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    • pp.427-430
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    • 1989
  • For on-line ARMA spectral estimation, the fast transversal filter algorithm of extended least squares method(ETS FTF) is presented. The projection operator, a key tool for geometric approach, is used in the derivation of the algorithm. ELS FTF is a fast time update recursion which is based on the fact that the correlation matrix of ARMA model satisfies the shift invariance property in each block, and thus it takes 10N+31 MADPR.

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A Study on Construction of Back-propagation Architecture for ARMA data (ARMA 데이터에 대한 Back-propagation 신경망의 구조)

  • 김나영;김희영
    • Proceedings of the Korean Statistical Society Conference
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    • pp.17-22
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    • 2000
  • 시계열 자료를 분석할 때 쉽게 접근하는 통계적 방법은 ARMA 모형이며 신경망 학습 방법 중에서는 다층 퍼셉트론에서의 Back-propagation 알고리즘이 일반적이다. Back-propagation을 비롯한 신경망 학습의 구조는 자료의 특성에 따라 경험적으로 결정하는 것으로 알려져 있다. 그러나 바로 이 점이 신경망 학습방법의 이용을 어렵게 하는 요인이기도 하다. 본 연구는 ARMA 모형 중 몇 개 유형의 자료에 대하여 Back-propagation 알고리즘을 적용함에 있어 어떠한 구조로 학습하는 것이 효율적인가를 입력층과 은닉층의 크기, 활성화 함수를 중심으로 검토하였다.

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Multivariate Autoregressive Moving Average(ARMA) process Control in Computer Integrated Manufacturing Systems (CIMS) (CIMS에서 다변량 ARMA 공정제어)

  • 최성운
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.15 no.26
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    • pp.181-187
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    • 1992
  • 본 논문은 CIMS에서 적응되는 ARMA 공정제어의 새로운 3단계절차를 제안한다. 첫번째 단계는 다변량 ARMA모델을 식별하여 모수를 추정하고, white noise로 진단된 잔차 series에 대하여 다변량 제어통계량(즉, 다변량 Hotelling T$^2$통계량, 다변량 CUSUM, 다변량 EWHA 통계량, 다변량 MA 통계량)등을 계산한다. 마지막으로 본 논문에서 제안한 8가지 다변량 제어통계량을 상호비교하여 이상점을 발견한다.

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On Strict Stationarity of Nonlinear Time Series Models without Irreducibility or Continuity Condition

  • Lee, Oe-Sook;Kim, Kyung-Hwa
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.1
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    • pp.211-218
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    • 2007
  • Nonlinear ARMA model $X_n\;=\;h(X_{n-1},{\cdots},X_{n-p},e_{n-1},{\cdots},e_{n-p})+e_n$ is considered and easy-to-check sufficient condition for strict stationarity of {$X_n$} without some irreducibility or continuity assumption is given. Threshold ARMA(p, q) and momentum threshold ARMA(p, q) models are examined as special cases.

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