Compact Numerical Methods for Computers: Linear Algebra and Function Minimisation
Autor John C. Nashen Limba Engleză Hardback – 28 iun 2018
New to the Second Edition
The accompanying software (available by coupon at no charge) includes not only the algorithm source codes, but also driver programs, example data, and several utility codes to help in the software engineering of end-user programs. The codes are designed for rapid implementation and reliable use in a wide variety of computing environments. Scientists, statisticians, engineers, and economists who prepare/modify programs for use in their work will find this resource invaluable. Moreover, since little previous training in numerical analysis is required, the book can also be used as a supplementary text for courses on numerical methods and mathematical software.
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Specificații
ISBN-13: 9781138413108
ISBN-10: 1138413100
Pagini: 290
Dimensiuni: 178 x 254 mm
Greutate: 0.7 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
ISBN-10: 1138413100
Pagini: 290
Dimensiuni: 178 x 254 mm
Greutate: 0.7 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
Public țintă
ProfessionalRecenzii
Praise for the first edition
"Anyone who must solve complex problems on a small computer would be well advised to consult Nash's book for both ideas and actual procedures. Those with the luxury of a large-scale computer for their numerical work will also find much of interest here."
-Peter Castro (Eastman Kodak), Technometrics, 22 February 1980
"Anyone who must solve complex problems on a small computer would be well advised to consult Nash's book for both ideas and actual procedures. Those with the luxury of a large-scale computer for their numerical work will also find much of interest here."
-Peter Castro (Eastman Kodak), Technometrics, 22 February 1980
Cuprins
A starting point Formal problems in linear algebra The singular-value decomposition and its use to solve least-squares problems Handling larger problems Some comments on the formation of the cross-product matrix ATA Linear equations-a direct approach The Choleski decomposition The symmetric positive definite matrix again The algebraic eigenvalue generalized problem Real symmetric matrices The generalized symmetric matrix eigenvalue problem Optimization and nonlinear equations One-dimensional problems Direct search methods Descent to a minimum I-variable metric algorithms Descent to a minimum II-conjugate gradients Minimizing a nonlinear sum of squares Leftovers The conjugate gradients method applied to problems in linear algebra Appendices Bibliography Index
Descriere
Designed to help people solve numerical problems on small computers, this book's main subject areas are numerical linear algebra, function minimization and root-finding. This edition has been revised and updated, the main difference being that the algorithms are presented in Turbo Pascal.