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Iterative Methods for Sparse Linear Systems

Iterative Methods for Sparse Linear Systems
Author: Yousef Saad
Publisher: SIAM
Total Pages: 537
Release: 2003-04-01
Genre: Mathematics
ISBN: 0898715342

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Mathematics of Computing -- General.


Direct Methods for Sparse Linear Systems

Direct Methods for Sparse Linear Systems
Author: Timothy A. Davis
Publisher: SIAM
Total Pages: 228
Release: 2006-09-01
Genre: Computers
ISBN: 0898716136

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The sparse backslash book. Everything you wanted to know but never dared to ask about modern direct linear solvers. Chen Greif, Assistant Professor, Department of Computer Science, University of British Columbia.Overall, the book is magnificent. It fills a long-felt need for an accessible textbook on modern sparse direct methods. Its choice of scope is excellent John Gilbert, Professor, Department of Computer Science, University of California, Santa Barbara.Computational scientists often encounter problems requiring the solution of sparse systems of linear equations. Attacking these problems efficiently requires an in-depth knowledge of the underlying theory, algorithms, and data structures found in sparse matrix software libraries. Here, Davis presents the fundamentals of sparse matrix algorithms to provide the requisite background. The book includes CSparse, a concise downloadable sparse matrix package that illustrates the algorithms and theorems presented in the book and equips readers with the tools necessary to understand larger and more complex software packages.With a strong emphasis on MATLAB and the C programming language, Direct Methods for Sparse Linear Systems equips readers with the working knowledge required to use sparse solver packages and write code to interface applications to those packages. The book also explains how MATLAB performs its sparse matrix computations.Audience This invaluable book is essential to computational scientists and software developers who want to understand the theory and algorithms behind modern techniques used to solve large sparse linear systems. The book also serves as an excellent practical resource for students with an interest in combinatorial scientific computing.Preface; Chapter 1: Introduction; Chapter 2: Basic algorithms; Chapter 3: Solving triangular systems; Chapter 4: Cholesky factorization; Chapter 5: Orthogonal methods; Chapter 6: LU factorization; Chapter 7: Fill-reducing orderings; Chapter 8: Solving sparse linear systems; Chapter 9: CSparse; Chapter 10: Sparse matrices in MATLAB; Appendix: Basics of the C programming language; Bibliography; Index.


Algorithms for Sparse Linear Systems

Algorithms for Sparse Linear Systems
Author: Jennifer Scott
Publisher: Springer Nature
Total Pages: 254
Release: 2023-04-29
Genre: Mathematics
ISBN: 3031258207

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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. It presents classical techniques for complete factorizations that are used in sparse direct methods and discusses the computation of approximate direct and inverse factorizations that are key to constructing general-purpose algebraic preconditioners for iterative solvers. A unified framework is used that emphasizes the underlying sparsity structures and highlights the importance of understanding sparse direct methods when developing algebraic preconditioners. Theoretical results are complemented by sparse matrix algorithm outlines. This monograph is aimed at students of applied mathematics and scientific computing, as well as computational scientists and software developers who are interested in understanding the theory and algorithms needed to tackle sparse systems. It is assumed that the reader has completed a basic course in linear algebra and numerical mathematics.


Direct Methods for Sparse Linear Systems

Direct Methods for Sparse Linear Systems
Author: Timothy A. Davis
Publisher: SIAM
Total Pages: 229
Release: 2006-01-01
Genre: Computers
ISBN: 9780898718881

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Presents the fundamentals of sparse matrix algorithms to provide the requisite background. The book includes CSparse, a concise downloadable sparse matrix package that illustrates the algorithms and theorems presented in the book and equips readers with the tools necessary to understand larger and more complex software packages.


Sparse Solutions of Underdetermined Linear Systems and Their Applications

Sparse Solutions of Underdetermined Linear Systems and Their Applications
Author: Ming-Jun Lai
Publisher: SIAM
Total Pages:
Release: 2021-06-25
Genre: Mathematics
ISBN: 1611976510

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This textbook presents a special solution to underdetermined linear systems where the number of nonzero entries in the solution is very small compared to the total number of entries. This is called a sparse solution. Since underdetermined linear systems can be very different, the authors explain how to compute a sparse solution using many approaches. Sparse Solutions of Underdetermined Linear Systems and Their Applications contains 64 algorithms for finding sparse solutions of underdetermined linear systems and their applications for matrix completion, graph clustering, and phase retrieval and provides a detailed explanation of these algorithms including derivations and convergence analysis. Exercises for each chapter help readers understand the material. This textbook is appropriate for graduate students in math and applied math, computer science, statistics, data science, and engineering. Advisors and postdoctoral scholars will also find the book interesting and useful.


Iterative Methods and Preconditioning for Large and Sparse Linear Systems with Applications

Iterative Methods and Preconditioning for Large and Sparse Linear Systems with Applications
Author: Daniele Bertaccini
Publisher: CRC Press
Total Pages: 321
Release: 2018-02-19
Genre: Mathematics
ISBN: 1351649612

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This book describes, in a basic way, the most useful and effective iterative solvers and appropriate preconditioning techniques for some of the most important classes of large and sparse linear systems. The solution of large and sparse linear systems is the most time-consuming part for most of the scientific computing simulations. Indeed, mathematical models become more and more accurate by including a greater volume of data, but this requires the solution of larger and harder algebraic systems. In recent years, research has focused on the efficient solution of large sparse and/or structured systems generated by the discretization of numerical models by using iterative solvers.


Iterative Methods for Sparse Linear Systems

Iterative Methods for Sparse Linear Systems
Author: Yousef Saad
Publisher: SIAM
Total Pages: 546
Release: 2003-01-01
Genre: Mathematics
ISBN: 9780898718003

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Since the first edition of this book was published in 1996, tremendous progress has been made in the scientific and engineering disciplines regarding the use of iterative methods for linear systems. The size and complexity of the new generation of linear and nonlinear systems arising in typical applications has grown. Solving the three-dimensional models of these problems using direct solvers is no longer effective. At the same time, parallel computing has penetrated these application areas as it became less expensive and standardized. Iterative methods are easier than direct solvers to implement on parallel computers but require approaches and solution algorithms that are different from classical methods. Iterative Methods for Sparse Linear Systems, Second Edition gives an in-depth, up-to-date view of practical algorithms for solving large-scale linear systems of equations. These equations can number in the millions and are sparse in the sense that each involves only a small number of unknowns. The methods described are iterative, i.e., they provide sequences of approximations that will converge to the solution.


Advances in Cryptology - CRYPTO '90

Advances in Cryptology - CRYPTO '90
Author: Alfred J. Menezes
Publisher: Springer
Total Pages: 630
Release: 2003-06-30
Genre: Computers
ISBN: 3540384243

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Crypto '90 marked the tenth anniversary of the Crypto conferences held at the University of California at Santa Barbara. The conference was held from August 11 to August 15, 1990 and was sponsored by the International Association for Cryptologic Research, in cooperation with the IEEE Computer Society Technical Committee on Security and Privacy and the Department of Computer Science of the University of California at Santa Barbara. 227 participants from twenty countries around the world. Crypto '90 attracted Roughly 35% of attendees were from academia, 45% from industry and 20% from government. The program was intended to provide a balance between the purely theoretical and the purely practical aspects of cryptography to meet the needs and diversified interests of these various groups. The overall organization of the conference was superbly handled by the general chairperson Sherry McMahan. All of the outstanding features of Crypto, which we have come to expect over the years, were again present and, in addition to all of this, she did a magnificent job in the preparation of the book of abstracts. This is a crucial part of the program and we owe her a great deal of thanks.


Sparsity Methods for Systems and Control

Sparsity Methods for Systems and Control
Author: Masaaki Nagahara
Publisher:
Total Pages: 220
Release: 2020-09-30
Genre:
ISBN: 9781680837247

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The method of sparsity has been attracting a lot of attention in the fields related not only to signal processing, machine learning, and statistics, but also systems and control. The method is known as compressed sensing, compressive sampling, sparse representation, or sparse modeling. More recently, the sparsity method has been applied to systems and control to design resource-aware control systems. This book gives a comprehensive guide to sparsity methods for systems and control, from standard sparsity methods in finite-dimensional vector spaces (Part I) to optimal control methods in infinite-dimensional function spaces (Part II). The primary objective of this book is to show how to use sparsity methods for several engineering problems. For this, the author provides MATLAB programs by which the reader can try sparsity methods for themselves. Readers will obtain a deep understanding of sparsity methods by running these MATLAB programs. Sparsity Methods for Systems and Control is suitable for graduate level university courses, though it should also be comprehendible to undergraduate students who have a basic knowledge of linear algebra and elementary calculus. Also, especially part II of the book should appeal to professional researchers and engineers who are interested in applying sparsity methods to systems and control.