Buch, Englisch, 128 Seiten, Format (B × H): 138 mm x 216 mm
Algorithms, Use Cases, and C++ Implementations
Buch, Englisch, 128 Seiten, Format (B × H): 138 mm x 216 mm
ISBN: 978-1-041-07334-5
Verlag: CRC Press
Linear Algebra for Localization emphasises the vital role of linear algebraic models in solving localization problems, as well as many other problems in algorithms, data science, and Artificial Intelligence. Localization has multi-industrial applications, which this book attempts to address through linear algebraic approaches while using the dominant C++ programming language in those industries.
Features
- Provides clear, illustrative descriptions of the main linear algebra topics and advanced algorithms in localization problems.
- C++ implementations available via associated GitHub repository, including detailed explanations, flowcharts, UML diagrams and text, and code runs output.
- Case study by the author for an advanced topics in automotive application.
Zielgruppe
Postgraduate and Undergraduate Advanced
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Preface Acronyms and Abbreviations Chapter 0 Introduction Chapter 1 Basic Matrix Operations Chapter 2 Special Matrices Chapter 3 Orthogonal Transformations Chapter 4 Matrix Factorization Chapter 5 Orthogonal Projections and Psudoinverse Chapter 6 Covariance Chapter 7 Singular Value Decomposition Chapter 8 Jacobian, Hessian, and Gradient Chapter 9 Fisher Information Matrix and the Cramér-Rao Lower Bound Chapter 10 Matrix Block Operations and Matrix Kernel Appendix A C++ Resources, Code Build, Code Run, and Code Debug Appendix B Case Study: Effect of Reference Points Locations on Cramér-Rao Lower Bound for Arbitrary Position Estimators




