Advances In Principal Component Analysis


Advances In Principal Component Analysis
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Advances In Principal Component Analysis


Advances In Principal Component Analysis
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Author : Ganesh R. Naik
language : en
Publisher: Springer
Release Date : 2017-12-11

Advances In Principal Component Analysis written by Ganesh R. Naik and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-11 with Technology & Engineering categories.


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.



Advances In Principal Component Analysis


Advances In Principal Component Analysis
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Author : Fausto Pedro García Márquez
language : en
Publisher:
Release Date : 2022

Advances In Principal Component Analysis written by Fausto Pedro García Márquez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Principal components analysis categories.




Principal Component Analysis


Principal Component Analysis
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Author : I.T. Jolliffe
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09

Principal Component Analysis written by I.T. Jolliffe and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.


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.



Advances In Principal Component Analysis


Advances In Principal Component Analysis
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Author : Fausto Pedro García Márquez
language : en
Publisher: BoD – Books on Demand
Release Date : 2022-08-25

Advances In Principal Component Analysis written by Fausto Pedro García Márquez and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-25 with Computers categories.


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.



Advances In Independent Component Analysis


Advances In Independent Component Analysis
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Author : Mark Girolami
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Advances In Independent Component Analysis written by Mark Girolami and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


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.



Principal Component Analysis


Principal Component Analysis
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Author : Virginia Gray
language : en
Publisher: Novinka Books
Release Date : 2017

Principal Component Analysis written by Virginia Gray and has been published by Novinka Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Factor analysis categories.


This book provides new research on principal component analysis (PCA). Chapter One introduces typical PCA applications of transcriptomic, proteomic and metabolomic data. Chapter Two studies the factor analysis of an outcome measurement survey for science, technology and society. Chapter Three examines the application of PCA to performance enhancement of hyperspectral radiative transfer computations.



Principal Component Analysis


Principal Component Analysis
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Author : Parinya Sanguansat
language : en
Publisher: BoD – Books on Demand
Release Date : 2012-03-07

Principal Component Analysis written by Parinya Sanguansat and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-07 with Computers categories.


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.



Measurement And Multivariate Analysis


Measurement And Multivariate Analysis
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Author : Shizuhiko Nishisato
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11

Measurement And Multivariate Analysis written by Shizuhiko Nishisato and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Mathematics categories.


Diversity is characteristic of the information age and also of statistics. To date, the social sciences have contributed greatly to the development of handling data under the rubric of measurement, while the statistical sciences have made phenomenal advances in theory and algorithms. Measurement and Multivariate Analysis promotes an effective interplay between those two realms of research-diversity with unity. The union and the intersection of those two areas of interest are reflected in the papers in this book, drawn from an international conference in Banff, Canada, with participants from 15 countries. In five major categories - scaling, structural analysis, statistical inference, algorithms, and data analysis - readers will find a rich variety of topics of current interest in the extended statistical community.



Generalized Principal Component Analysis


Generalized Principal Component Analysis
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Author : René Vidal
language : en
Publisher: Springer
Release Date : 2016-04-11

Generalized Principal Component Analysis written by René Vidal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-11 with Science categories.


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.



Force Control Theory And Method Of Human Load Carrying Exoskeleton Suit


Force Control Theory And Method Of Human Load Carrying Exoskeleton Suit
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Author : Zhiyong Yang
language : en
Publisher: Springer
Release Date : 2017-04-06

Force Control Theory And Method Of Human Load Carrying Exoskeleton Suit written by Zhiyong Yang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-06 with Technology & Engineering categories.


This book reports on the latest advances in concepts and further development of principal component analysis (PCA), discussing in detail a number of open problems related to dimensional reduction techniques and their extensions. It brings together research findings, previously scattered throughout many scientific journal papers worldwide, and 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 focusing on open problems, it is essential reading for all researchers and practitioners with an interest in PCA