Isermann, Rolf
Identification of Dynamic Systems An introduction with Applications Rolf Isermann, Marco Münchhof - xxv, 705 páginas : ilustraciones 24 cm.
Incluye referencias bibliográficas e índice.
Theoretical and Experimental Modeling – Tasks and Problems for the Identification of Dynamic Systems – Mathematical Models of Linear Dynamic Systems and Stochastic Signals – Identification of Non-Parametric Models in the Frequency Domain- Continuous Time Signals – Spectral Analysis Methods for Periodic and Non-Periodic Signals – Frequency Response Measurement for Periodic Test Signals – Identification of Non-Parametric Models with Correlation Analysis- Continuous and Discrete Time – Correlation Analysis with Continuous Time Models – Correlation Analysis with Discrete time Models – Identification with Parametric Models- Discrete Time Signals – Identification with Parametric Models- Continuous Time Signals – Identification of Multi-Variable Systems – Identification of Multi-Variable Systems – Identification of Non-Linear Systems – Iterative Optimization – Neural Networks and Lookup Tables for Identification – State and Parameter Estimation by Kalman Filtering – Miscellaneous Issues – Numerical Aspects – Practical Aspects of Parameter Estimation – Applications –Appendix --
9783540788782
System identification--Mathematical models
Identificación del sistema moderno matemático
Sistemas dinamicos
003.1 / Is2i
Identification of Dynamic Systems An introduction with Applications Rolf Isermann, Marco Münchhof - xxv, 705 páginas : ilustraciones 24 cm.
Incluye referencias bibliográficas e índice.
Theoretical and Experimental Modeling – Tasks and Problems for the Identification of Dynamic Systems – Mathematical Models of Linear Dynamic Systems and Stochastic Signals – Identification of Non-Parametric Models in the Frequency Domain- Continuous Time Signals – Spectral Analysis Methods for Periodic and Non-Periodic Signals – Frequency Response Measurement for Periodic Test Signals – Identification of Non-Parametric Models with Correlation Analysis- Continuous and Discrete Time – Correlation Analysis with Continuous Time Models – Correlation Analysis with Discrete time Models – Identification with Parametric Models- Discrete Time Signals – Identification with Parametric Models- Continuous Time Signals – Identification of Multi-Variable Systems – Identification of Multi-Variable Systems – Identification of Non-Linear Systems – Iterative Optimization – Neural Networks and Lookup Tables for Identification – State and Parameter Estimation by Kalman Filtering – Miscellaneous Issues – Numerical Aspects – Practical Aspects of Parameter Estimation – Applications –Appendix --
9783540788782
System identification--Mathematical models
Identificación del sistema moderno matemático
Sistemas dinamicos
003.1 / Is2i