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 a downloadable EResource at www.routledge.com/9781041073345, including detailed explanations, flowcharts, UML diagrams and text, and code runs output.
- Case study by the author for an advanced topics in automotive application.
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.
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
Ahmed Al-Muraeb is an electrical engineer with over 22 years of multi-industrial and academic experience. He holds a Ph.D. in Electrical and Computer Engineering from Oakland University, Michigan, USA (2016), an M.Sc. in Laser Applications in Electronic Engineering from the University of Baghdad, Baghdad, Iraq (2004), and a B.Sc. in Electronics and Communication Engineering from the University of Baghdad, Baghdad, Iraq (2000).
Ahmed has extensive industrial experience, including positions at MOTOROLA and Nokia-Siemens Networks, and has been working on ADAS/AD features development and testing including localization solutions verification and validation, hardware components validation, and delivery of hardware and software products for General Motors, Ford, and Geely. He holds over 65 professional trainings and certifications, including the 31-course General Motors Validation Engineer Apprentice certification (2019).
In academia, Ahmed has taught courses in communication systems, electronics, and VLSI design at Wayne State University and Oakland University in Michigan, USA, and at the University of Baghdad, Iraq. His research includes two dissertationson tunable fiber laser system design and quantum cryptography using polarization-entangled photon pairsas well as six journal and conference publications in lasers and photonics. He has received eight awards and grants, including from IEEE and SPIE.
Ahmed is a Senior IEEE member and a lifelong member of Sigma Xi The Scientific Research Honor Society. He is passionate about sharing knowledge in clear and accessible ways. In his free time, he enjoys art, reading, hiking, and music.
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