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Author: J. V. Scheidt
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3112721853
Category : Mathematics
Languages : en
Pages : 272
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Book Description
No detailed description available for "Random Eigenvalue Problems".
Author: J. V. Scheidt
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3112721853
Category : Mathematics
Languages : en
Pages : 272
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Book Description
No detailed description available for "Random Eigenvalue Problems".
Author:
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Category : Aeronautics
Languages : en
Pages : 702
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Category : Mechanics, Applied
Languages : en
Pages : 776
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Category : Statistics
Languages : en
Pages : 652
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Book Description
Author: Yousef Saad
Publisher: SIAM
ISBN: 9781611970739
Category : Mathematics
Languages : en
Pages : 292
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Book Description
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 Each chapter was updated by shortening or deleting outdated topics, adding topics of more recent interest, and adapting the Notes and References section.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.
Author: Society for Industrial and Applied Mathematics
Publisher:
ISBN:
Category : Electronic journals
Languages : en
Pages : 838
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Book Description
Contains research articles on mathematical methods and their applications in the physical, engineering, biological, and medical sciences.
Author: M. L. Mehta
Publisher: Academic Press
ISBN: 1483258564
Category : Mathematics
Languages : en
Pages : 270
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Book Description
Random Matrices and the Statistical Theory of Energy Levels focuses on the processes, methodologies, calculations, and approaches involved in random matrices and the statistical theory of energy levels, including ensembles and density and correlation functions. The publication first elaborates on the joint probability density function for the matrix elements and eigenvalues, including the Gaussian unitary, symplectic, and orthogonal ensembles and time-reversal invariance. The text then examines the Gaussian ensembles, as well as the asymptotic formula for the level density and partition function. The manuscript elaborates on the Brownian motion model, circuit ensembles, correlation functions, thermodynamics, and spacing distribution of circular ensembles. Topics include continuum model for the spacing distribution, thermodynamic quantities, joint probability density function for the eigenvalues, stationary and nonstationary ensembles, and ensemble averages. The publication then examines the joint probability density functions for two nearby spacings and invariance hypothesis and matrix element correlations. The text is a valuable source of data for researchers interested in random matrices and the statistical theory of energy levels.
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Category : Dissertations, Academic
Languages : en
Pages : 946
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Author: László Erdős
Publisher: American Mathematical Soc.
ISBN: 1470436485
Category : Mathematics
Languages : en
Pages : 239
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Book Description
A co-publication of the AMS and the Courant Institute of Mathematical Sciences at New York University This book is a concise and self-contained introduction of recent techniques to prove local spectral universality for large random matrices. Random matrix theory is a fast expanding research area, and this book mainly focuses on the methods that the authors participated in developing over the past few years. Many other interesting topics are not included, and neither are several new developments within the framework of these methods. The authors have chosen instead to present key concepts that they believe are the core of these methods and should be relevant for future applications. They keep technicalities to a minimum to make the book accessible to graduate students. With this in mind, they include in this book the basic notions and tools for high-dimensional analysis, such as large deviation, entropy, Dirichlet form, and the logarithmic Sobolev inequality. This manuscript has been developed and continuously improved over the last five years. The authors have taught this material in several regular graduate courses at Harvard, Munich, and Vienna, in addition to various summer schools and short courses. Titles in this series are co-published with the Courant Institute of Mathematical Sciences at New York University.
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Category : Science
Languages : en
Pages : 552
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