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Eigenvalues

  • Numerical Methods for Eigenvalue Problemsby Steffen Börm; Christian Mehl

    De Gruyter 2012; US$ 34.95

    Eigenvalues and eigenvectors of matrices and linear operators play an important role when solving problems from structural mechanics and electrodynamics, e.g., by describing the resonance frequencies of systems, when investigating the long-term behavior of stochastic processes, e.g., by describing invariant probability measures, and as... more...

  • Geršgorin and His Circlesby Richard S Varga

    Springer Berlin Heidelberg 2010; US$ 129.32

    TheGer? sgorin CircleTheorem, averywell-known resultin linear algebra today, stems from the paper of S. Ger? sgorin in 1931 (which is reproduced in AppendixD)where,givenanarbitraryn×ncomplexmatrix,easyarithmetic operationsontheentriesofthematrixproducendisks,inthecomplexplane, whose union contains all eigenvalues of the given matrix. The beauty and... more...

  • Symplectic Methods for the Symplectic Eigenproblemby Heike Fassbender

    Springer US 2007; US$ 141.08

    The solution of eigenvalue problems is an integral part of many scientific computations. For example, the numerical solution of problems in structural dynamics, electrical networks, macro-economics, quantum chemistry, and c- trol theory often requires solving eigenvalue problems. The coefficient matrix of the eigenvalue problem may be small to medium... more...

  • Extremum Problems for Eigenvalues of Elliptic Operatorsby Antoine Henrot

    Birkhäuser Basel 2006; US$ 50.55

    Problems linking the shape of a domain or the coefficients of an elliptic operator to the sequence of its eigenvalues are among the most fascinating of mathematical analysis. In this book, we focus on extremal problems. For instance, we look for a domain which minimizes or maximizes a given eigenvalue of the Laplace operator with various boundary... more...

  • Eigenvalues, Inequalities, and Ergodic Theoryby Mu-Fa Chen

    Springer London 2006; US$ 88.17

    A problem of broad interest – the estimation of the spectral gap for matrices or differential operators (Markov chains or diffusions) – is covered in this book. The area has a wide range of applications, and provides a tool to describe the phase transitions and the effectiveness of random algorithms. In particular, the book studies a subset of the... more...

  • Numerical Methods for General and Structured Eigenvalue Problemsby Daniel Kressner

    Springer Berlin Heidelberg 2006; US$ 141.08

    The purpose of this book is to describe recent developments in solving eig- value problems, in particular with respect to the QR and QZ algorithms as well as structured matrices. Outline Mathematically speaking, the eigenvalues of a square matrix A are the roots of its characteristic polynomial det(A??I). An invariant subspace is a linear subspace... more...

  • Inverse Eigenvalue Problemsby Moody Chu; Gene Golub

    OUP Oxford 2005; US$ 169.99

    Inverse eigenvalue problems arise in a remarkable variety of applications and associated with any inverse eigenvalue problem are two fundamental questions—the theoretical issue of solvability and the practical issue of computability. Both questions are difficult and challenging. In this text, the authors discuss the fundamental questions, some known... more...

  • Non-Self-Adjoint Boundary Eigenvalue Problemsby R. Mennicken; M. Möller

    Elsevier Science 2003; US$ 235.00

    This monograph provides a comprehensive treatment of expansion theorems for regular systems of first order differential equations and n -th order ordinary differential equations. In 10 chapters and one appendix, it provides a comprehensive treatment from abstract foundations to applications in physics and engineering. The focus is on non-self-adjoint... more...

  • Large Scale Eigenvalue Problemsby J. Cullum; R. A. Willoughby

    Elsevier Science 1986; US$ 72.95

    Results of research into large scale eigenvalue problems are presented in this volume. The papers fall into four principal categories: novel algorithms for solving large eigenvalue problems, novel computer architectures, computationally-relevant theoretical analyses, and problems where large scale eigenelement computations have provided new insight.... more...

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