System Identification: A Frequency Domain Approach
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More About This Title System Identification: A Frequency Domain Approach
English
About the Authors Rik Pintelon and Johan Schoukens are professors of electrical engineering at the Vrije Universiteit Brussels, Brussels, Belgium. They share research interests in system identification, signal processing, and measurement techniques. They are the coauthors of a software package with a user-friendly graphical user interface called Frequency Domain System Identification Toolbox for Matlab(r), which covers the methods discussed in this book.
English
Preface.
Acknowledgments.
List of Operators and National Conventions.
List of Symbols.
List of Abbreviations.
An Introduction to Identification.
Measurements of Frequency Response Functions.
Frequency Response Function Measurements in the Presence of Nonlinear Distortions.
Design of Excitation Signals.
Models of Linear Time-Invariant Systems.
An Intuitive Introduction to Frequency Domain Identification.
Estimation with Known Noise Model.
Estimation with Unknown Noise Model.
Model Selection and Validation.
Base Choices in System Identification.
Guidelines for the User.
Applications.
Some Linear Algebra Fundamentals.
Some Probability and Stochastic Convergence Fundamentals.
Properties of Least Squares Estimators with Deterministic Weighting.
Properties of Least Squares Estimators with Stochastic Weighting.
Identification of Semilinear Models.
Identification of Invariant of (Over) Parameterized Models.
References.
Subject Index.
Reference Index.
About the Authors.
Acknowledgments.
List of Operators and National Conventions.
List of Symbols.
List of Abbreviations.
An Introduction to Identification.
Measurements of Frequency Response Functions.
Frequency Response Function Measurements in the Presence of Nonlinear Distortions.
Design of Excitation Signals.
Models of Linear Time-Invariant Systems.
An Intuitive Introduction to Frequency Domain Identification.
Estimation with Known Noise Model.
Estimation with Unknown Noise Model.
Model Selection and Validation.
Base Choices in System Identification.
Guidelines for the User.
Applications.
Some Linear Algebra Fundamentals.
Some Probability and Stochastic Convergence Fundamentals.
Properties of Least Squares Estimators with Deterministic Weighting.
Properties of Least Squares Estimators with Stochastic Weighting.
Identification of Semilinear Models.
Identification of Invariant of (Over) Parameterized Models.
References.
Subject Index.
Reference Index.
About the Authors.
