Principles of system identification theory and practice
Presents the foundational pillars of identification, namely, the theory of discrete-time LTI systems, the basics of signal processing, the theory of random processes, and estimation theory
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| Format: | Book |
| Language: | English |
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Table of Contents:
- Introduction
- A journey into identification
- Mathematical descriptions of processes: models
- Models for discrete-time LTI systems
- Transform-domain models for linear Time-invariant systems
- Sampling and discretization
- Random processes
- Time-domain analysis: correlation functions
- Models for linear stationary processes
- Fourier analysis and spectral analysis of deterministic signals
- Spectral representations of random processes
- Introduction to estimation
- Goodness of estimators
- Estimation methods: part I
- Estimation methods: part II
- Estimation of signal properties
- Non-parametric and parametric models for identification
- Predictions
- Identification of parametric time-series models
- Identification of non-parametric input-output models
- Identification of parametric input-output models
- Statistical and practical elements of model building
- Identification of state-space models
- Case studies
- Advanced topics in SISO identification
- Linear multivariable identification