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Advances in Principal Component Anal...
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SpringerLink (Online service)
Advances in Principal Component Analysis = Research and Development /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Advances in Principal Component Analysis/ edited by Ganesh R. Naik.
Reminder of title:
Research and Development /
other author:
Naik, Ganesh R.
Description:
VII, 252 p. 94 illus., 75 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Signal processing. -
Online resource:
https://doi.org/10.1007/978-981-10-6704-4
ISBN:
9789811067044
Advances in Principal Component Analysis = Research and Development /
Advances in Principal Component Analysis
Research and Development /[electronic resource] :edited by Ganesh R. Naik. - 1st ed. 2018. - VII, 252 p. 94 illus., 75 illus. in color.online resource.
Theory -- Basic principles of PCA -- Geometric Principles of PCA -- Principal components and Correlation -- PCA in Regression analysis matrices -- PCA in cluster analysis -- PCA and factor analysis -- PCA for time series and independent data (ICA) -- Sparse PCA -- Non-negative PCA -- Applications of PCA -- PCA for Electrocardiography (ECG) applications -- PCA for Electroencephalography (EEG) applications -- PCA for Electromyography (EMG) applications -- PCA for bioinformatics and gene expression applications -- PCA for human movement science applications -- PCA for Gait Kinematics for Patients with Knee Osteoarthritis -- Neuroscience and biomedical application of PCA -- PCA applications for Brain Computer Interface (BCI) and motor imagery tasks -- PCA for Image processing applications -- PCA for Video processing applications -- PCA for dimensional reduction applications -- PCA for financial and economics applications.
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.
ISBN: 9789811067044
Standard No.: 10.1007/978-981-10-6704-4doiSubjects--Topical Terms:
561459
Signal processing.
LC Class. No.: TK5102.9
Dewey Class. No.: 621.382
Advances in Principal Component Analysis = Research and Development /
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Theory -- Basic principles of PCA -- Geometric Principles of PCA -- Principal components and Correlation -- PCA in Regression analysis matrices -- PCA in cluster analysis -- PCA and factor analysis -- PCA for time series and independent data (ICA) -- Sparse PCA -- Non-negative PCA -- Applications of PCA -- PCA for Electrocardiography (ECG) applications -- PCA for Electroencephalography (EEG) applications -- PCA for Electromyography (EMG) applications -- PCA for bioinformatics and gene expression applications -- PCA for human movement science applications -- PCA for Gait Kinematics for Patients with Knee Osteoarthritis -- Neuroscience and biomedical application of PCA -- PCA applications for Brain Computer Interface (BCI) and motor imagery tasks -- PCA for Image processing applications -- PCA for Video processing applications -- PCA for dimensional reduction applications -- PCA for financial and economics applications.
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