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Linear Algebra for Localization: Algorithms, Use Cases, and C++ Implementations

Autor Ahmed Al-Muraeb
en Limba Engleză Hardback – 23 feb 2026
This book emphasizes 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
  • This book provides clear, illustrative descriptions of the main linear algebra topics and advanced algorithms in localization problems.
  • It provides C++ implementations available via the associated eResource repository, including detailed explanations, flowcharts, UML diagrams and text, and code run output.
  • It also provides case studies by the author for advanced topics in automotive applications.
 
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Specificații

ISBN-13: 9781041073345
ISBN-10: 1041073348
Pagini: 162
Ilustrații: 76
Dimensiuni: 138 x 216 mm
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC

Public țintă

Postgraduate and Undergraduate Advanced

Notă biografică

Ahmed Al-Muraeb is an electrical engineer with approximately two decades of multi-industrial and academic experience, with Ph.D. (Oakland University, MI, USA, in 2016) and M.Sc. (University of Baghdad, Baghdad, Iraq, in 2004) degrees. His industrial experience spanned cellular RF networks operation, maintenance, system admin, and database; cellular value-added services configuration, operations, and admin; and automotive ADAS/AD features development and testing, as well as hardware components validation, with 30+ certifications and trainings. Ahmed’s ADAS/AD experience includes localization solutions since 2020 and continuing. His academic experience comprises teaching (at Wayne State University, Michigan, USA, and Oakland University) and research (in lasers and photonics), with publications (two dissertations and six journal and conference papers) and awards (eight grants and awards).
In addition to his industrial and academic achievements, Ahmed is passionate about sharing his knowledge in the clearest, most comprehensive, and accurate form and making complex topics accessible to a broader audience. In his free time, Ahmed enjoys making art, reading, hiking, watching documentaries, movies, and shows, and listening to music.

Cuprins

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            

Descriere

This book 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.