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The Recursive Identification of Stochastic Linear Dynamical Systems Simulation Study | ||
| IRAQI JOURNAL OF STATISTICAL SCIENCES | ||
| Article 4, Volume 11, Issue 1, 2011, Pages 31-54 PDF (0 K) | ||
| DOI: 10.33899/iqjoss.2011.028368 | ||
| Abstract | ||
| 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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