Equivalent Continuous-Time Representation of Autoregressive-Moving Average Model

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  • 自己回帰移動平均モデルの連続時間実現
  • ジコ カイキ イドウ ヘイキン モデル ノ レンゾク ジカン ジツゲン

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The transformation of linear continuous-time system model into discrete-time one is amenable to direct solution for both deterministic and stochastic situations. In this paper, the reverse problem is investigated, and a procedure is developed for performing the transformation from an autoregressive moving-average (ARMA) model to an equivalent minimal order continuous-time system with a white noise input in the sense that the correlation function of the continuous-time model is identical at the samping instance with that of the corresponding ARMA process. The technique presented here is found useful in area where the systems are actually continuous, but the fact that the available data are discrete leads to identification of ARMA model.

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