• Title Numerical Methods for Large Eigenvalue Problems, Revised Edition
• Author(s) Yousef Saad
• Publisher: SIAM - Society for Industrial & Applied Mathematics; Revised edition edition (May 17, 2011)
• Hardcover/Paperback: 292 pages
• eBook: PDF
• Language: English
• ISBN-10: 1611970725
• ISBN-13: 978-1611970722
• Share This:  

Book Description

This book is intended for researchers in applied mathematics and scientific computing as well as for practitioners interested in understanding the theory of numerical methods used for eigenvalue problems. It also can be used as a supplemental text for an advanced graduate-level course on these methods.

This revised edition discusses numerical methods for computing eigenvalues and eigenvectors of large sparse matrices. It provides an in-depth view of the numerical methods that are applicable for solving matrix eigenvalue problems that arise in various engineering and scientific applications. Each chapter was updated by shortening or deleting outdated topics, adding topics of more recent interest, and adapting the Notes and References section.

Significant changes have been made to Chapters 6 through 8, which describe algorithms and their implementations and now include topics such as the implicit restart techniques, the Jacobi-Davidson method, and automatic multilevel substructuring.

• Yousef Saad is a College of Science and Engineering distinguished professor in the Department of Computer Science at the University of Minnesota. His current research interests include numerical linear algebra, sparse matrix computations, iterative methods, parallel computing, numerical methods for electronic structure, and data analysis. He is a Fellow of SIAM and the AAAS.

• Amazon

• Numerical Analysis and Scientific Computing
• Algebra, Abstract Algebra, and Linear Algebra, etc.
• Fortran Programming Language
• Parallel Computing and Programming
• Computational and Algorithmic Mathematics

• Numerical Methods for Large Eigenvalue Problems, Revised Edition (Yousef Saad)
• The Mirror Site (1) - PDF
• The Mirror Site (2) - PDF
• Book Homepage (Other Formats, Other Books, etc.)

• Iterative Methods for Sparse Linear Systems (Yousef Saad)

  This book is a practical algorithms for solving large-scale linear systems of equations using Iterative Methods. Numerous exercises have been added, as well as an updated and expanded bibliography.

• Algorithms for Sparse Linear Systems (Jennifer Scott, et al.)

  Large sparse linear systems of equations are ubiquitous in science, engineering and beyond. This open access monograph focuses on factorization algorithms for solving such systems.

• Lecture Notes of Matrix Computations (Wen-Wei Lin)

  Thoroughly details matrix computations and the accompanying theory alongside the author's useful insights, This book provides a clear and thorough introduction to matrix computations,a key component of scientific computing.

• Architecture of Advanced Numerical Analysis Systems

  This unique open access book applies the functional OCaml programming language to numerical or computational weighted data science, engineering, and scientific applications. It's based on Owl, an OCaml-based numerical computing library.

• Tea Time Numerical Analysis: Experiences in Mathematics

  This textbook was born of a desire to contribute a viable, free, introductory Numerical Analysis textbook. The ultimate goal of this book is to be a complete, one-semester, single-pdf, downloadable textbook designed for mathematics classes.

• Introduction to Numerical Methods for Variational Problems

  This textbook teaches Finite Element Methods from a computational point of view. It focuses on how to develop flexible computer programs with Python, a programming language in which a combination of symbolic and numerical tools.

• First Semester in Numerical Analysis with Python (Yaning Liu)

  This book introduces students to Numerical Methods using Python for the implementation of the algorithms. Discusses several common applications of Numerical Analysis and implementation using real world examples and hands on programming exercises.

• The Art of Polynomial Interpolation (Stuart Murphy)

  Exploring the techniques of interpolating data allows us to view the development and birth of a polynomial. This book is focused on laying a foundation for understanding and applying several common forms of Polynomial Interpolation.

• Numerical Algorithms: Computer Vision, Machine Learning, etc.

  This book presents a new approach to numerical analysis for modern computer scientists, covers a wide range of topics - from numerical linear algebra to optimization and differential equations - focusing on real-world motivation and unifying themes.

• Numerical Methods and MATLAB Programming for Engineers

  It covers the fundamentals while emphasizing the most essential numerical methods. Readers will enhance their programming skills using MATLAB to implement algorithms, discover how to use MATLAB to solve problems in science and engineering.

• Numerical Methods with Applications, 2nd Edition (Autar K Kaw)

  This book entitled Numerical Methods with Applications is written primarily for engineering undergraduates taking a course in Numerical Methods. It offers a unique treatise to numerical methods which is based on a holistic approach and short chapters.

• Parallel Spectral Numerical Methods (Gong Chen, et al)

  This book teaches the principals of Fourier spectral methods, their utility in solving partial differential equation and how to implement them in code. The programs will use Matlab and Fortran. A Python implementation of some of the Matlab programs is also provided.