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논문검색

Construction of the Kalman Filter Algorithm on the Model Reduction

초록

영어

In this paper we derive a state variable estimation method of discrete stochastic dynamical systems. It aims to obtain accurate estimation with short computing time. Therefore, the point of this paper is to discuss a construction of Kalman filter algorithm on the reduced model. First, we construct a reduced model by using balanced truncation method. Further, we apply state variable estimation steps of discrete stochastic dynamical systems by using Kalman filter on the reduced model. Thus, Kalman filter algorithm will be constructed on the reduced model.

목차

Abstract
 1. Introduction
 2. The Algorithm of Kalman Filter on the Discrete System
 3. Reduced Model Construction on the Discrete Systems
 4. The Algorithm of Kalman Filter on the Reduced Model
 5. Case study
 6. Conclusions
 Acknowledgements
 References

저자정보

  • Didik Khusnul Arif Post Graduate Student in Department of Mathematics, Universitas Gadjah Mada (UGM), Yogyakarta, Indonesia, Department of Mathematics, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia.
  • Widodo Department of Mathematics, Universitas Gadjah Mada (UGM), Yogyakarta, Indonesia.
  • Salmah Department of Mathematics, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia.
  • Erna Apriliani Department of Mathematics, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia.

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