Generalized Principal Component Analysis (Paperback, Softcover reprint of the original 1st ed. 2016)

This book provides a comprehensive introduction to the latest advances in the mathematical theory and computational tools for modeling high-dimensional data drawn from one or multiple low-dimensional subspaces (or manifolds) and potentially corrupted by noise, gross errors, or outliers. This challenging task requires the development of new algebraic, geometric, statistical, and computational methods for efficient and robust estimation and segmentation of one or multiple subspaces. The book also presents interesting real-world applications of these new methods in image processing, image and video segmentation, face recognition and clustering, and hybrid system identification etc. This book is intended to serve as a textbook for graduate students and beginning researchers in data science, machine learning, computer vision, image and signal processing, and systems theory. It contains ample illustrations, examples, and exercises and is made largely self-contained with three Appendices which survey basic concepts and principles from statistics, optimization, and algebraic-geometry used in this book. Rene Vidal is a Professor of Biomedical Engineering and Director of the Vision Dynamics and Learning Lab at The Johns Hopkins University. Yi Ma is Executive Dean and Professor at the School of Information Science and Technology at ShanghaiTech University. S. Shankar Sastry is Dean of the College of Engineering, Professor of Electrical Engineering and Computer Science and Professor of Bioengineering at the University of California, Berkeley.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Interdisciplinary Applied Mathematics, 40
Release date:	April 2018
First published:	2016
Authors:	Rene Vidal • Yi Ma • Shankar Sastry
Dimensions:	235 x 155 x 32mm (L x W x T)
Format:	Paperback
Pages:	566
Edition:	Softcover reprint of the original 1st ed. 2016
ISBN-13:	978-1-4939-7912-7
Categories:	Books > Science & Mathematics > Science: general issues > General Books > Computing & IT > General theory of computing > General Books > Computing & IT > Computer software packages > Multimedia Books > Reference & Interdisciplinary > Communication studies > Information theory > Cybernetics & systems theory Books > Science & Mathematics > Mathematics > Algebra > General Books > Science & Mathematics > Mathematics > Applied mathematics > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > General Books > Computing & IT > Applications of computing > Image processing > General
LSN:	1-4939-7912-4
Barcode:	9781493979127

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