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This edition presents Jonathan Swift's most important Irish writings in both prose and verse, together with an introduction, head notes and annotations that shed new light on the full context and significance of each piece. Familiar works such as Constructive Nonlinear Control presents a broad repertoire of constructive nonlinear designs not available in other works by widening the class of systems and design tools.
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Several streams of nonlinear control theory are merged and directed toward The algorithmic techniques developed may be useful anytime a model leads to a mathematical optimization problem where the domain naturally is a manifold, particularly if the manifold is a matrix manifold. The book follows the usual definition-theorem-proof style but it is not intended for traditional course work so there are no exercises.
- Optimization Algorithms on Matrix Manifolds.
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A reader with limited exposure to manifold theory and differential geometry most likely will benefit from consulting standard texts on those subjects first. Every chapter starts with a page-long introduction clearly outlining its goals and how they are achieved together with possible relations to other chapters.https://taguscucomna.gq/beautiful-crocheted-afghans-5.php
P.A. Absil (Author of Optimization Algorithms on Matrix Manifolds)
I find the material very well explained and supported with appropriate examples. It is a pleasure to work with such a book. Trendafilov, Foundations of Computational Mathematics. Absil is associate professor of mathematical engineering at the Universite Catholique de Louvain in Belgium.
Two more theoretical chapters provide readers with the background in differential geometry necessary to algorithmic development.
In the other chapters, several well-known optimization methods such as steepest descent and conjugate gradients are generalized to abstract manifolds. The book provides a generic development of each of these methods, building upon the material of the geometric chapters. It then guides readers through the calculations that turn these geometrically formulated methods into concrete numerical algorithms. The state-of-the-art algorithms given as examples are competitive with the best existing algorithms for a selection of eigenspace problems in numerical linear algebra.
It can serve as a graduate-level textbook and will be of interest to applied mathematicians, engineers, and computer scientists. Absil is associate professor of mathematical engineering at the Universite Catholique de Louvain in Belgium. Mahony is reader in engineering at the Australian National University. Sepulchre is professor of electrical engineering and computer science at the University of Liege in Belgium.
Line-Search Algorithms on Manifolds 54 4. Second-Order Geometry 91 5. Newton's Method 6.
Trust-Region Methods 7. A Constellation of Superlinear Algorithms 8.
Optimization algorithms on matrix manifolds
Rayleigh quotient minimization 8. Nielsen Book Data Publisher's Summary Many problems in the sciences and engineering can be rephrased as optimization problems on matrix search spaces endowed with a so-called manifold structure. This book shows how to exploit the special structure of such problems to develop efficient numerical algorithms.
It places careful emphasis on both the numerical formulation of the algorithm and its differential geometric abstraction - illustrating how good algorithms draw equally from the insights of differential geometry, optimization, and numerical analysis. Two more theoretical chapters provide readers with the background in differential geometry necessary to algorithmic development.
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