Advances In Principal Component Analysis

Author : Ganesh R. Naik
Publisher : Springer
ISBN 13 : 981106704X
Total Pages : 252 pages
Book Rating : 4.44/5 ( download)

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Download or read book Advances in Principal Component Analysis written by Ganesh R. Naik and published by Springer. This book was released on 2017-12-11 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports on the latest advances in concepts and further developments of principal component analysis (PCA), addressing a number of open problems related to dimensional reduction techniques and their extensions in detail. Bringing together research results previously scattered throughout many scientific journals papers worldwide, the book presents them in a methodologically unified form. Offering vital insights into the subject matter in self-contained chapters that balance the theory and concrete applications, and especially focusing on open problems, it is essential reading for all researchers and practitioners with an interest in PCA.

Author : Fausto Pedro García Márquez
Publisher :
ISBN 13 : 9781803557670
Total Pages : 0 pages
Book Rating : 4.72/5 ( download)

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Download or read book Advances in Principal Component Analysis written by Fausto Pedro García Márquez and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : I.T. Jolliffe
Publisher : Springer Science & Business Media
ISBN 13 : 1475719043
Total Pages : 283 pages
Book Rating : 4.48/5 ( download)

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Download or read book Principal Component Analysis written by I.T. Jolliffe and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principal component analysis is probably the oldest and best known of the It was first introduced by Pearson (1901), techniques ofmultivariate analysis. and developed independently by Hotelling (1933). Like many multivariate methods, it was not widely used until the advent of electronic computers, but it is now weIl entrenched in virtually every statistical computer package. The central idea of principal component analysis is to reduce the dimen sionality of a data set in which there are a large number of interrelated variables, while retaining as much as possible of the variation present in the data set. This reduction is achieved by transforming to a new set of variables, the principal components, which are uncorrelated, and which are ordered so that the first few retain most of the variation present in all of the original variables. Computation of the principal components reduces to the solution of an eigenvalue-eigenvector problem for a positive-semidefinite symmetrie matrix. Thus, the definition and computation of principal components are straightforward but, as will be seen, this apparently simple technique has a wide variety of different applications, as weIl as a number of different deri vations. Any feelings that principal component analysis is a narrow subject should soon be dispelled by the present book; indeed some quite broad topics which are related to principal component analysis receive no more than a brief mention in the final two chapters.

Author : Mark Girolami
Publisher : Springer Science & Business Media
ISBN 13 : 1447104439
Total Pages : 286 pages
Book Rating : 4.38/5 ( download)

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Download or read book Advances in Independent Component Analysis written by Mark Girolami and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Independent Component Analysis (ICA) is a fast developing area of intense research interest. Following on from Self-Organising Neural Networks: Independent Component Analysis and Blind Signal Separation, this book reviews the significant developments of the past year. It covers topics such as the use of hidden Markov methods, the independence assumption, and topographic ICA, and includes tutorial chapters on Bayesian and variational approaches. It also provides the latest approaches to ICA problems, including an investigation into certain "hard problems" for the very first time. Comprising contributions from the most respected and innovative researchers in the field, this volume will be of interest to students and researchers in computer science and electrical engineering; research and development personnel in disciplines such as statistical modelling and data analysis; bio-informatic workers; and physicists and chemists requiring novel data analysis methods.

Author : Fausto Pedro García Márquez
Publisher : BoD – Books on Demand
ISBN 13 : 1803557656
Total Pages : 254 pages
Book Rating : 4.56/5 ( download)

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Download or read book Advances in Principal Component Analysis written by Fausto Pedro García Márquez and published by BoD – Books on Demand. This book was released on 2022-08-25 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes and discusses the use of principal component analysis (PCA) for different types of problems in a variety of disciplines, including engineering, technology, economics, and more. It presents real-world case studies showing how PCA can be applied with other algorithms and methods to solve both large and small and static and dynamic problems. It also examines improvements made to PCA over the years.

Author : René Vidal
Publisher : Springer
ISBN 13 : 0387878114
Total Pages : 566 pages
Book Rating : 4.19/5 ( download)

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Download or read book Generalized Principal Component Analysis written by René Vidal and published by Springer. This book was released on 2016-04-11 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. René 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.

Author : George H. Dunteman
Publisher : SAGE
ISBN 13 : 9780803931046
Total Pages : 98 pages
Book Rating : 4.42/5 ( download)

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Download or read book Principal Components Analysis written by George H. Dunteman and published by SAGE. This book was released on 1989-05 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: For anyone in need of a concise, introductory guide to principal components analysis, this book is a must. Through an effective use of simple mathematical-geometrical and multiple real-life examples (such as crime statistics, indicators of drug abuse, and educational expenditures) -- and by minimizing the use of matrix algebra -- the reader can quickly master and put this technique to immediate use.

Author : Parinya Sanguansat
Publisher : BoD – Books on Demand
ISBN 13 : 953510182X
Total Pages : 234 pages
Book Rating : 4.26/5 ( download)

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Download or read book Principal Component Analysis written by Parinya Sanguansat and published by BoD – Books on Demand. This book was released on 2012-03-07 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is aimed at raising awareness of researchers, scientists and engineers on the benefits of Principal Component Analysis (PCA) in data analysis. In this book, the reader will find the applications of PCA in fields such as energy, multi-sensor data fusion, materials science, gas chromatographic analysis, ecology, video and image processing, agriculture, color coating, climate and automatic target recognition.

Author : K. I. Diamantaras
Publisher : Wiley-Interscience
ISBN 13 :
Total Pages : 282 pages
Book Rating : 4.96/5 ( download)

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Download or read book Principal Component Neural Networks written by K. I. Diamantaras and published by Wiley-Interscience. This book was released on 1996-03-08 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systematically explores the relationship between principal component analysis (PCA) and neural networks. Provides a synergistic examination of the mathematical, algorithmic, application and architectural aspects of principal component neural networks. Using a unified formulation, the authors present neural models performing PCA from the Hebbian learning rule and those which use least squares learning rules such as back-propagation. Examines the principles of biological perceptual systems to explain how the brain works. Every chapter contains a selected list of applications examples from diverse areas.

Author : J. Edward Jackson
Publisher : John Wiley & Sons
ISBN 13 : 0471725323
Total Pages : 597 pages
Book Rating : 4.29/5 ( download)

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Download or read book A User's Guide to Principal Components written by J. Edward Jackson and published by John Wiley & Sons. This book was released on 2005-01-21 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. From the Reviews of A User’s Guide to Principal Components "The book is aptly and correctly named–A User’s Guide. It is the kind of book that a user at any level, novice or skilled practitioner, would want to have at hand for autotutorial, for refresher, or as a general-purpose guide through the maze of modern PCA." –Technometrics "I recommend A User’s Guide to Principal Components to anyone who is running multivariate analyses, or who contemplates performing such analyses. Those who write their own software will find the book helpful in designing better programs. Those who use off-the-shelf software will find it invaluable in interpreting the results." –Mathematical Geology