The Recursive Identification of Stochastic Linear Dynamical Systems Simulation Study
This Paper deals with the recursive identification problem of stochastic linear dynamical systems , Important Algorithms are explained in the identification system domains that are time-varying, and using a recursive Least Square method with a famous approach to estimate the model parameter, that a...
| Format: | Article |
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| Language: | Arabic |
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College of Computer Science and Mathematics, University of Mosul
2011-06-01
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| Series: | المجلة العراقية للعلوم الاحصائية |
| Online Access: | https://stats.mosuljournals.com/article_28368_cf8f38c6cf3d7c4f6235fc8d26dd087a.pdf |
| Summary: | This Paper deals with the recursive identification problem of stochastic linear dynamical systems , Important Algorithms are explained in the identification system domains that are time-varying, and using a recursive Least Square method with a famous approach to estimate the model parameter, that a forgetting factor, and a Kalman filter approach with different values for a best linear dynamic models, that are identified from the two type of stochastic linear dynamic systems: that the equation error models which contain ARX models and ARMAX models. Output error models which consist of OE and Box-Jenkins models, that are reached by using the suggested instrument in Off-Line Identification, where the exact Linear models reached their parameter stable with Time, Moreover, the Statistic terms are verified from a point of random errors and insignificant cross-correlation between inputs and outputs residual. |
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| ISSN: | 1680-855X 2664-2956 |