Introduction to applied linear algebra : vectors, matrices, and least squares
Author(s)
Bibliographic Information
Introduction to applied linear algebra : vectors, matrices, and least squares
Cambridge University Press, 2018
- : hardback
Available at / 30 libraries
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University of Tsukuba Library, Library on Library and Information Science
: hardback411.35-B6910020016257
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Hokkaido University, Faculty and Graduate School of Engineering図書
: hardback512.5/B6923580336454
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Note
Includes index
Description and Table of Contents
Description
This groundbreaking textbook combines straightforward explanations with a wealth of practical examples to offer an innovative approach to teaching linear algebra. Requiring no prior knowledge of the subject, it covers the aspects of linear algebra - vectors, matrices, and least squares - that are needed for engineering applications, discussing examples across data science, machine learning and artificial intelligence, signal and image processing, tomography, navigation, control, and finance. The numerous practical exercises throughout allow students to test their understanding and translate their knowledge into solving real-world problems, with lecture slides, additional computational exercises in Julia and MATLAB (R), and data sets accompanying the book online. Suitable for both one-semester and one-quarter courses, as well as self-study, this self-contained text provides beginning students with the foundation they need to progress to more advanced study.
Table of Contents
- Part I. Vectors: 1. Vectors
- 2. Linear functions
- 3. Norm and distance
- 4. Clustering
- 5. Linear independence
- Part II. Matrices: 6. Matrices
- 7. Matrix examples
- 8. Linear equations
- 9. Linear dynamical systems
- 10. Matrix multiplication
- 11. Matrix inverses
- Part III. Least Squares: 12. Least squares
- 13. Least squares data fitting
- 14. Least squares classification
- 15. Multi-objective least squares
- 16. Constrained least squares
- 17. Constrained least squares applications
- 18. Nonlinear least squares
- 19. Constrained nonlinear least squares
- Appendix A
- Appendix B
- Appendix C
- Appendix D
- Index.
by "Nielsen BookData"