Pages that link to "Item:Q2241739"
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The following pages link to A novel recursive learning identification scheme for Box-Jenkins model based on error data (Q2241739):
Displaying 8 items.
- Recursive Bayesian algorithm with covariance resetting for identification of Box-Jenkins systems with non-uniformly sampled input data (Q308072) (← links)
- A novel weight function-based robust iterative learning identification method for discrete Box-Jenkins models with Student's \(t\)-distribution noises (Q682739) (← links)
- Recursive least squares identification of hybrid Box-Jenkins model structure in open-loop and closed-loop (Q1660885) (← links)
- Parameter estimation for a controlled autoregressive autoregressive moving average system based on a recursive framework (Q2110838) (← links)
- Box-Jenkins identification revisited. II: Applications (Q2641731) (← links)
- Parameter identification of Bouc–Wen type models using a modified experience-based learning algorithm (Q6048035) (← links)
- Separable synthesis gradient estimation methods and convergence analysis for multivariable systems (Q6099494) (← links)
- A new adaptive identification framework for nonlinear multi-input multi-output systems under colored noise (Q6135577) (← links)
