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Titre : System identification : theory for the User Type de document : texte imprime Auteurs : L. Ljung Mention d'édition : 2nd ed. Editeur : Englewood Cliffs : Prentice Hall Année de publication : cop. 1999 Importance : (XXII-609 p.) Présentation : ill. Format : 24 cm ISBN/ISSN/EAN : 978-0-13-656695-3 Note générale : Autre(s) tirage(s) : 2006
Bibliogr. p. 565-593. IndexLangues : Français Mots-clés : Systems Algorithms Estimation Simulation Prediction Identification Neural networks Neuro- fuzzy modeling Résumé :
Appropriate for courses in System Identification. This book is a comprehensive and coherent description of the theory, methodology and practice of System Identification―the science of building mathematical models of dynamic systems by observing input/output data. It puts the user in focus, giving the necessary background to understand theoretical foundation and emphasizing the practical aspects of the options and choices that face the user. The Second Edition has been updated to include material on subspace methods, non-linear black box models―such as neural networks―and methods that use frequency domain data.Note de contenu :
1. Introduction
Part I. Systems and models
2. Time-invariant linear systems
3. Simulation and prediction
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. Convergence and consistency
9. Asymptotic distribution of parameter estimators
10. Computing the estimate
11. Recursive estimation methods
Part III. User's choices
12. Options and objectives
13. Experiment design
14. Preprocessing data
15. Choice of identification criterion
16. Model structure selection and model validation
17. System identification in practice
Appendix I. Some concepts form probability theory
Appendix II. Some statistical techniques for linear regressions
En ligne : https://www.amazon.fr/System-Identification-Theory-Lennart-Ljung/dp/0136566952/r [...] Permalink : ./index.php?lvl=notice_display&id=9468 System identification : theory for the User [texte imprime] / L. Ljung . - 2nd ed. . - Englewood Cliffs : Prentice Hall, cop. 1999 . - (XXII-609 p.) : ill. ; 24 cm.
ISBN : 978-0-13-656695-3
Autre(s) tirage(s) : 2006
Bibliogr. p. 565-593. Index
Langues : Français
Mots-clés : Systems Algorithms Estimation Simulation Prediction Identification Neural networks Neuro- fuzzy modeling Résumé :
Appropriate for courses in System Identification. This book is a comprehensive and coherent description of the theory, methodology and practice of System Identification―the science of building mathematical models of dynamic systems by observing input/output data. It puts the user in focus, giving the necessary background to understand theoretical foundation and emphasizing the practical aspects of the options and choices that face the user. The Second Edition has been updated to include material on subspace methods, non-linear black box models―such as neural networks―and methods that use frequency domain data.Note de contenu :
1. Introduction
Part I. Systems and models
2. Time-invariant linear systems
3. Simulation and prediction
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. Convergence and consistency
9. Asymptotic distribution of parameter estimators
10. Computing the estimate
11. Recursive estimation methods
Part III. User's choices
12. Options and objectives
13. Experiment design
14. Preprocessing data
15. Choice of identification criterion
16. Model structure selection and model validation
17. System identification in practice
Appendix I. Some concepts form probability theory
Appendix II. Some statistical techniques for linear regressions
En ligne : https://www.amazon.fr/System-Identification-Theory-Lennart-Ljung/dp/0136566952/r [...] Permalink : ./index.php?lvl=notice_display&id=9468 Réservation
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