Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgements
- Part I Lectures on Basics with Examples
- 1 A First Example: Optimal Quadratic Control
- 2 Dynamical Systems
- 3 LTV (Quasi-separable) Systems
- 4 System Identification
- 5 State Equivalence, State Reduction
- 6 Elementary Operations
- 7 Inner Operators and External Factorizations
- 8 Inner−Outer Factorization
- 9 The Kalman Filter as an Application
- 10 Polynomial Representations
- 11 Quasi-separable Moore−Penrose Inversion
- Part II Further Contributions to Matrix Theory
- Appendix: Data Model and Implementations
- References
- Index
6 - Elementary Operations
from Part I - Lectures on Basics with Examples
Published online by Cambridge University Press: 24 October 2024
- Frontmatter
- Contents
- Preface
- Acknowledgements
- Part I Lectures on Basics with Examples
- 1 A First Example: Optimal Quadratic Control
- 2 Dynamical Systems
- 3 LTV (Quasi-separable) Systems
- 4 System Identification
- 5 State Equivalence, State Reduction
- 6 Elementary Operations
- 7 Inner Operators and External Factorizations
- 8 Inner−Outer Factorization
- 9 The Kalman Filter as an Application
- 10 Polynomial Representations
- 11 Quasi-separable Moore−Penrose Inversion
- Part II Further Contributions to Matrix Theory
- Appendix: Data Model and Implementations
- References
- Index
Summary
This chapter is on elementary matrix operations using a state-space or, equivalently, quasi-separable representation. It is a straightforward but unavoidable chapter. It shows how the recursive structure of the state-space representations is exploited to make matrix addition, multiplication and elementary inversion numerically efficient. The notions of outer operator and inner operator are introduced as basic types of matrices playing a central role in various specific matrix decompositions and factorizations to be treated in further chapters.
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- Time-Variant and Quasi-separable SystemsMatrix Theory, Recursions and Computations, pp. 87 - 94Publisher: Cambridge University PressPrint publication year: 2024