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1. Introduction.
PART I. SYSTEMS AND MODELS.
2. Time-Invariant Linear Systems.
3. Simulation, Prediction, and Control.
4. Models of Linear Time-Invariant Systems.
5. Models for Time-Varying and Nonlinear Systems.
PART II. METHODS.
6. Nonparametric Time- and Frequency-Domain Methods.
7.Parameter Estimation Methods.
8.Covergence and Consistency.
9. Asymptotic Distribution of Parameter Estimates.
10. Computing the Estimate.
11. Recursive Estimation Methods.
PART III. USER'S CHOICES.
12. Options and Objectives.
13. Affecting the Bias Distribution of Transfer-Function Estimates.
14. Experiment Design.
15. Choice of Identification Criterion.
16. Model Structure Selection and Model Validation.
17. System Identification in Practice.
Appendix I. Some Concepts from Probability Theory.
Appendix II. Some Statistical Techniques for Linear Regressions.
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Add System Identification: Theory for the User, The field's leading text, now completely updated. Modeling dynamical systems — theory, methodology, and applications. Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, a, System Identification: Theory for the User to the inventory that you are selling on WonderClubX
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Add System Identification: Theory for the User, The field's leading text, now completely updated. Modeling dynamical systems — theory, methodology, and applications. Lennart Ljung's System Identification: Theory for the User is a complete, coherent description of the theory, methodology, a, System Identification: Theory for the User to your collection on WonderClub |