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Více informací o knize Conjugate Gradient Algorithms in Nonconvex Optimization

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Anotace knihy

This up-to-date book is on algorithms for large-scale unconstrained and bound constrained optimization. Optimization techniques are shown from a conjugate gradient algorithm perspective. Large part of the book is devoted to preconditioned conjugate gradient algorithms. In particular memoryless and limited memory quasi-Newton algorithms are presented and numerically compared to standard conjugate gradient algorithms. The special attention is paid to the methods of shortest residuals developed by the author. Several effective optimization techniques based on these methods are presented. Because of the emphasis on practical methods, as well as rigorous mathematical treatment of their convergence analysis, the book is aimed at a wide audience. It can be used by researches in optimization, graduate students in operations research, engineering, mathematics and computer science. Practitioners can benefit from numerous numerical comparisons of professional optimization codes discussed in the book.

Parametry knihy

Zařazení knihy Knihy v angličtině Mathematics & science Mathematics Calculus & mathematical analysis

• Plný název: Conjugate Gradient Algorithms in Nonconvex Optimization
• Autor: Radoslaw Pytlak
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 478
• EAN: 9783540856337
• ISBN: 3540856331
• ID: 01570519
• Nakladatelství: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
• Hmotnost: 916 g
• Rozměry: 235 × 155 × 31 mm
• Datum vydání: 01. November 2008

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