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Exploiting Hidden Structure in Matrix Computations: Algorithms and Applications

Focusing on special matrices and matrices which are in some sense `near' to structured matrices, this volume covers a broad range of topics;

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Matrix Computations and Semiseparable Matrices - Eigenvalve and Singular Value Methods V2

The general properties and mathematical structures of semiseparable matrices were presented in volume 1 of Matrix Computations and;

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Fundamentals of Matrix Computations

Fundamentals of Matrix Computations deals with the concept of matrix computations, a technique of singular value homogenization and its;

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Quaternion Matrix Computations

In this monograph, the authors describe state-of-the-art real structure-preserving algorithms for quaternion matrix computations;

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Numerical Methods in Matrix Computations

Matrix algorithms are at the core of scientific computing and are indispensable tools in most applications in engineering. This book offers;

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Matrix Algorithms

This thorough, concise, and superbly written volume is the first in a self-contained five-volume series devoted to matrix algorithms. It;

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Fundamentals of Matrix Computations

This new, modernized edition provides a clear and thorough introduction to matrix computations,a key component of scientific computing;

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Matrices, Moments and Quadrature with Applications

bilinear forms involving two vectors and a function of the matrix. The first part of the book provides the necessary mathematical background and;

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Matrix Algorithms in MATLAB

demonstrate code usage and the properties of the presented algorithms. Despite the wide availability of computer programs for matrix computations, it;

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Matrix Algebra

Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. This much-needed work;

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Matrix Algebra

Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. This much-needed work;

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Structure-Preserving Doubling Algorithms for Nonlinear Matrix Equations

Nonlinear matrix equations arise frequently in applied science and engineering. This is the first book to provide a unified treatment;

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Structured Matrix Based Methods for Approximate Polynomial GCD

computations, the polynomial GCD problem can be expressed in matrix form: the second part of the book focuses on this point of view and analyses the;

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Numerical Computations: Theory and Algorithms

The two-volume set LNCS 11973 and 11974 constitute revised selected papers from the Third International Conference on Numerical;

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Fast Solvers for Mesh-Based Computations

matrix. All the solvers presented are either designed from scratch or based on previously designed and implemented solvers. Each chapter also;

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Matrix Theory and Applications With Matlab

Designed for use in a second course on linear algebra, Matrix Theory and Applications with MATLAB covers the basics of the subject-from a;

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Parallel Scientific Computing and Optimization

Parallel Scientific Computing and Optimization introduces new developments in the construction, analysis, and implementation of parallel;

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Linear Algebra and Matrix Computations with MATLAB (R)

This book focuses the solutions of linear algebra and matrix analysis problems, with the exclusive use of MATLAB. The topics include;

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Combinatorial Scientific Computing

optimization, algorithmic differentiation of numerical simulation code, sparse matrix software tools, and combinatorial challenges and applications;

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Combinatorial Scientific Computing

optimization, algorithmic differentiation of numerical simulation code, sparse matrix software tools, and combinatorial challenges and applications;

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Computing

of computers. The study of algorithmics is contained in Part II including matrix computations, fundamental algorithms and data structures, design and;

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Design and Analysis of Algorithms

introduction, the book provides a detailed account of graphs and data structure. It then discusses matrix algorithms, basic algorithms, network;

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Fast Algorithms For Signal Processing

Efficient signal processing algorithms are important for embedded and power-limited applications since, by reducing the number;

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Optimization Algorithms on Matrix Manifolds

Many problems in the sciences and engineering can be rephrased as optimization problems on matrix search spaces endowed with a so-called;

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Parallel Processing and Applied Mathematics

; applications of parallel computing; soft computing with applications; and special session on parallel matrix factorizations. Part II: workshop on;

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Parallel Processing and Applied Mathematics

of parallel computing; soft computing with applications; and special session on parallel matrix factorizations. Part II: workshop on models;

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Fundamentals of Matrix Computations

A significantly revised and improved introduction to a critical aspect of scientific computationMatrix computations lie at the heart;

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