Matrix Analysis and Computations introduces the basics of matrix analysis and presents representative methods and their corresponding theories in matrix computations. In this textbook, readers will find:
The matrix theory necessary for direct and iterative methods for solving systems of linear equations.
Systematic methods and rigorous theory on matrix splitting iteration methods and Krylov subspace iteration methods.
Current results on preconditioning and iterative methods for solving standard and generalized saddle-point linear systems.
Exercises at the end of each chapter for applying learned methods.
This book is intended for graduate students, researchers, and engineers interested in matrix analysis and matrix computations. It is appropriate for the following courses: Advanced Numerical Analysis, Special Topics on Numerical Analysis, Topics on Data Science, Topics on Numerical Optimization, and Topics on Approximation Theory.
