Exact and Approximate Modeling of Linear Systems
Exact and Approximate Modeling of Linear Systems: A Behavioral Approach elegantly introduces the behavioral approach to mathematical modeling, an approach that requires models to be viewed as sets of possible outcomes rather than to be a priori bound to particular representations. The authors discuss exact and approximate fitting of data by linear, bilinear, and quadratic static models and linear dynamic models, a formulation that enables readers to select the most suitable representation for a particular purpose. This book presents exact subspace-type and approximate optimization-based identification methods, as well as representation-free problem formulations, an overview of solution approaches, and software implementation. Readers will find an exposition of a wide variety of modeling problems starting from observed data. The presented theory leads to algorithms that are implemented in C language and in MATLAB.
- Elegantly introduces the behavioral approach to mathematical modeling
- Presents exact subspace-type and approximate optimization-based identification methods
- Includes algorithms that are implemented in C language and in MATLAB
Product details
January 2006Paperback
9780898716030
184 pages
253 × 178 × 13 mm
0.402kg
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Table of Contents
- Preface
- 1. Introduction
- 2. Approximate modeling via misfit minimization
- Part I. Static Problems:
- 3. Weighted total least squares
- 4. Structured total least squares
- 5. Bilinear errors-in-variables model
- 6. Ellipsoid fitting
- Part II. Dynamic Problems:
- 7. Introduction to dynamical models
- 8. Exact identification
- 9. Balanced model identification
- 10. Errors-in-variables smoothing and filtering
- 11. Approximate system identification
- 12. Conclusions
- Appendices
- Notation
- Bibliography
- Index.