Parallel Numerical Computation with Applications

Parallel Numerical Computation with Applications

Author: Laurence Tianruo Yang

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 234

ISBN-13: 1461552052

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Parallel Numerical Computations with Applications contains selected edited papers presented at the 1998 Frontiers of Parallel Numerical Computations and Applications Workshop, along with invited papers from leading researchers around the world. These papers cover a broad spectrum of topics on parallel numerical computation with applications; such as advanced parallel numerical and computational optimization methods, novel parallel computing techniques, numerical fluid mechanics, and other applications related to material sciences, signal and image processing, semiconductor technology, and electronic circuits and systems design. This state-of-the-art volume will be an up-to-date resource for researchers in the areas of parallel and distributed computing.


Introduction to Applied Linear Algebra

Introduction to Applied Linear Algebra

Author: Stephen Boyd

Publisher: Cambridge University Press

Published: 2018-06-07

Total Pages: 477

ISBN-13: 1316518965

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A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.


Solving Irregularly Structured Problems in Parallel

Solving Irregularly Structured Problems in Parallel

Author: Gianfranco Bilardi

Publisher: Springer Science & Business Media

Published: 1997-06-04

Total Pages: 306

ISBN-13: 9783540631385

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This book constitutes the refereed proceedings of the 4th International Symposium on Solving Irregularly Structured Problems in Parallel, IRREGULAR'97, held in Paderborn, Germany, in June 1997. The 18 revised full papers presented were carefully selected by the program committee for inclusion in the volume; also included are full papers by the five invited speakers. Among the topics covered are discrete algorithms, randomized methods and approximation algorithms, implementations, programming environments, systems and applications, and scheduling and load balancing.


Data-Driven Identification of Networks of Dynamic Systems

Data-Driven Identification of Networks of Dynamic Systems

Author: Michel Verhaegen

Publisher: Cambridge University Press

Published: 2022-05-12

Total Pages: 288

ISBN-13: 100902809X

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This comprehensive text provides an excellent introduction to the state of the art in the identification of network-connected systems. It covers models and methods in detail, includes a case study showing how many of these methods are applied in adaptive optics and addresses open research questions. Specific models covered include generic modelling for MIMO LTI systems, signal flow models of dynamic networks and models of networks of local LTI systems. A variety of different identification methods are discussed, including identification of signal flow dynamics networks, subspace-like identification of multi-dimensional systems and subspace identification of local systems in an NDS. Researchers working in system identification and/or networked systems will appreciate the comprehensive overview provided, and the emphasis on algorithm design will interest those wishing to test the theory on real-life applications. This is the ideal text for researchers and graduate students interested in system identification for networked systems.


Applied Parallel Computing. Industrial Computation and Optimization

Applied Parallel Computing. Industrial Computation and Optimization

Author: Jerzy Wasniewski

Publisher: Springer Science & Business Media

Published: 1996-12-11

Total Pages: 744

ISBN-13: 9783540620952

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Although the last decade has witnessed significant advances in control theory for finite and infinite dimensional systems, the stability and control of time-delay systems have not been fully investigated. Many problems exist in this field that are still unresolved, and there is a tendency for the numerical methods available either to be too general or too specific to be applied accurately across a range of problems. This monograph brings together the latest trends and new results in this field, with the aim of presenting methods covering a large range of techniques. Particular emphasis is placed on methods that can be directly applied to specific problems. The resulting book is one that will be of value to both researchers and practitioners.


Linear Algebra, Rational Approximation and Orthogonal Polynomials

Linear Algebra, Rational Approximation and Orthogonal Polynomials

Author: A. Bultheel

Publisher: Elsevier

Published: 1997-11-17

Total Pages: 465

ISBN-13: 0080535526

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Evolving from an elementary discussion, this book develops the Euclidean algorithm to a very powerful tool to deal with general continued fractions, non-normal Padé tables, look-ahead algorithms for Hankel and Toeplitz matrices, and for Krylov subspace methods. It introduces the basics of fast algorithms for structured problems and shows how they deal with singular situations.Links are made with more applied subjects such as linear system theory and signal processing, and with more advanced topics and recent results such as general bi-orthogonal polynomials, minimal Padé approximation, polynomial root location problems in the complex plane, very general rational interpolation problems, and the lifting scheme for wavelet transform computation. The text serves as a supplement to existing books on structured linear algebra problems, rational approximation and orthogonal polynomials.Features of this book:• provides a unifying approach to linear algebra, rational approximation and orthogonal polynomials• requires an elementary knowledge of calculus and linear algebra yet introduces advanced topics.The book will be of interest to applied mathematicians and engineers and to students and researchers.


Vector Extrapolation Methods with Applications

Vector Extrapolation Methods with Applications

Author: Avram Sidi

Publisher: SIAM

Published: 2017-09-26

Total Pages: 421

ISBN-13: 161197495X

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An important problem that arises in different disciplines of science and engineering is that of computing limits of sequences of vectors of very large dimension. Such sequences arise, for example, in the numerical solution of systems of linear and nonlinear equations by fixed-point iterative methods, and their limits are simply the required solutions to these systems. The convergence of these sequences, which is very slow in many cases, can be accelerated successfully by using suitable vector extrapolation methods. Vector Extrapolation Methods with Applications?is the first book fully dedicated to the subject of vector extrapolation methods. It is a self-contained, up-to-date, and state-of-the-art reference on the theory and practice of the most useful methods. It covers all aspects of the subject, including development of the methods, their convergence study, numerically stable algorithms for their implementation, and their various applications. It also provides complete proofs in most places. As an interesting application, the author shows how these methods give rise to rational approximation procedures for vector-valued functions in the complex plane, a subject of importance in model reduction problems among others. This book is intended for numerical analysts, applied mathematicians, and computational scientists and engineers in fields such as computational fluid dynamics, structures, and mechanical and electrical engineering, to name a few. Since it provides complete proofs in most places, it can also serve as a textbook in courses on acceleration of convergence of iterative vector processes, for example.


Numerical Methods for General and Structured Eigenvalue Problems

Numerical Methods for General and Structured Eigenvalue Problems

Author: Daniel Kressner

Publisher: Springer Science & Business Media

Published: 2006-01-20

Total Pages: 272

ISBN-13: 3540285024

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This book is about computing eigenvalues, eigenvectors, and invariant subspaces of matrices. Treatment includes generalized and structured eigenvalue problems and all vital aspects of eigenvalue computations. A unique feature is the detailed treatment of structured eigenvalue problems, providing insight on accuracy and efficiency gains to be expected from algorithms that take the structure of a matrix into account.