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Computational unconstrained nonlinear optimization comes to life from a study of the interplay between the metric-based (Cauchy) and model-based (Newton) points of view. The motivating problem is that of minimizing a convex quadratic function. This research monograph reveals for the first time the essential unity of the subject. It explores the relationships between the main methods, develops the Newton-Cauchy framework and points out its rich wealth of algorithmic implications and basic conceptual methods. The monograph also makes a valueable contribution to unifying the notation and terminology of the subject. It is addressed topractitioners, researchers, instructors, and students and provides a useful and refreshing new perspective on computational nonlinear optimization.
| Autorius: | John L. Nazareth |
| Serija: | Lecture Notes in Computer Science |
| Leidėjas: | Springer Berlin Heidelberg |
| Išleidimo metai: | 1994 |
| Knygos puslapių skaičius: | 120 |
| ISBN-10: | 3540576711 |
| ISBN-13: | 9783540576716 |
| Formatas: | 235 x 155 x 7 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „The Newton-Cauchy Framework: A Unified Approach to Unconstrained Nonlinear Minimization“
