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Zusatztext 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 Informationen zum Autor John C. Nash Klappentext Focusing on reliable, compact algorithms for computational problems, this book considers specific mathematical problems of wide applicability, develops approaches to a solution and the consequent algorithm, and provides the program steps. It emphasizes useful applicable methods from various scientific research fields, ranging from mathematical physics to commodity production modeling. This edition now presents program steps as Turbo Pascal code, includes more algorithmic examples, and contains an extended bibliography. The accompanying software includes algorithm source codes, driver programs, example data, and utility codes to aid in the software engineering of end-user programs. Zusammenfassung 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. Inhaltsverzeichnis 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...
