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Global Variational Analysis: Weierstrass Integrals on a Riemannian Manifold. (MN-16), Morse Marston


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Автор: Morse Marston
Название:  Global Variational Analysis: Weierstrass Integrals on a Riemannian Manifold. (MN-16)
ISBN: 9780691617251
Издательство: Wiley
Классификация:
ISBN-10: 0691617252
Обложка/Формат: Paperback
Страницы: 270
Вес: 0.46 кг.
Дата издания: 08.03.2015
Серия: Mathematical notes
Язык: English
Иллюстрации: Black & white illustrations
Размер: 254 x 178 x 15
Читательская аудитория: Tertiary education (us: college)
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: This book builds upon the revolutionary discovery made in 1974 that when one passes from function f to a function J of paths joining two points A1?A1 the connectivities R1 of the domain of f can be replaced by connectivities R1 over Q, common to the pathwise components of a basic Frechet space of classes of equivalent curves joining A1 to A1. The c


Manifold Learning Theory and Applications

Автор: Ma
Название: Manifold Learning Theory and Applications
ISBN: 1439871094 ISBN-13(EAN): 9781439871096
Издательство: Taylor&Francis
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Цена: 22202.00 р.
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Описание:

Trained to extract actionable information from large volumes of high-dimensional data, engineers and scientists often have trouble isolating meaningful low-dimensional structures hidden in their high-dimensional observations. Manifold learning, a groundbreaking technique designed to tackle these issues of dimensionality reduction, finds widespread application in machine learning, neural networks, pattern recognition, image processing, and computer vision.

Filling a void in the literature, Manifold Learning Theory and Applications incorporates state-of-the-art techniques in manifold learning with a solid theoretical and practical treatment of the subject. Comprehensive in its coverage, this pioneering work explores this novel modality from algorithm creation to successful implementation--offering examples of applications in medical, biometrics, multimedia, and computer vision. Emphasizing implementation, it highlights the various permutations of manifold learning in industry including manifold optimization, large scale manifold learning, semidefinite programming for embedding, manifold models for signal acquisition, compression and processing, and multi scale manifold.

Beginning with an introduction to manifold learning theories and applications, the book includes discussions on the relevance to nonlinear dimensionality reduction, clustering, graph-based subspace learning, spectral learning and embedding, extensions, and multi-manifold modeling. It synergizes cross-domain knowledge for interdisciplinary instructions, offers a rich set of specialized topics contributed by expert professionals and researchers from a variety of fields. Finally, the book discusses specific algorithms and methodologies using case studies to apply manifold learning for real-world problems.

Riemannian Topology and Geometric Structures on Manifolds

Автор: Krzysztof Galicki; Santiago R. Simanca
Название: Riemannian Topology and Geometric Structures on Manifolds
ISBN: 0817647422 ISBN-13(EAN): 9780817647421
Издательство: Springer
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Цена: 20962.00 р.
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Описание: The various contributions to this volume discuss recent advances in the areas of positive sectional curvature, Kahler and Sasakian geometry, and their interrelation to mathematical physics, especially M and superstring theory.

Existence and Regularity of Minimal Surfaces on Riemannian Manifolds. (MN-27):

Автор: Pitts Jon T.
Название: Existence and Regularity of Minimal Surfaces on Riemannian Manifolds. (MN-27):
ISBN: 0691615004 ISBN-13(EAN): 9780691615004
Издательство: Wiley
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Описание: Mathematical No/ex, 27 Originally published in 1981. The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paper


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