Algorithms for Sparse Linear Systems by Jennifer Scott
Book Contents :-
1. An Introduction to Sparse Matrices
2. Sparse Matrices and Their Graphs
3. Introduction to Matrix Factorizations
4. Sparse Cholesky Solver: The Symbolic Phase
5. Sparse Cholesky Solver: The Factorization Phase
6. Sparse LU Factorizations
7. Stability, Ill-Conditioning, and Symmetric Indefinite Factorizations
8. Sparse Matrix Ordering Algorithms
9. Algebraic Preconditioners and Approximate Factorizations
10. Incomplete Factorizations
11. Sparse Approximate Inverse Preconditioners
Correction to: Algorithms for Sparse Linear Systems
About this book :-
This book focuses on methods for solving large systems of linear equations where most elements are zero. These "sparse" systems are common in fields like engineering, physics, and computer science. The book introduces techniques for breaking down these systems into simpler parts, making them easier to solve. It covers both exact and approximate methods, helping readers understand how to efficiently handle large, sparse problems. This monograph is aimed at students of applied mathematics and scientific computing, as well as computational scientists and software developers interested in understanding the theory and algorithms needed to tackle sparse systems.
Book Detail :-
Title:
Algorithms for Sparse Linear Systems by Jennifer Scott
Publisher:
Birkhäuser
Year:
2023
Pages:
264
Type:
PDF
Language:
English
ISBN-10 #:
3031258193
ISBN-13 #:
978-3031258190
License:
CC BY 4.0
Amazon:
Amazon
About Author :-
The author
Jennifer Ann Scott
(born in 1960) is a British mathematician. She focuses on numerical analysis, working with sparse matrices, and parallel computing. She is a professor of applied mathematics at the University of Reading, where she leads the Centre for the Mathematics of Planet Earth. She also works as a Group Leader and Research Fellow at the Rutherford Appleton Laboratory for the Science and Technology Facilities Council.
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