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Advances in Principal Component Analysis

Research and Development

Specificaties
Gebonden, blz. | Engels
Springer Nature Singapore | e druk, 2018
ISBN13: 9789811067037
Rubricering
Springer Nature Singapore e druk, 2018 9789811067037
€ 144,99
Levertijd ongeveer 8 werkdagen

Samenvatting

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.

Specificaties

ISBN13:9789811067037
Taal:Engels
Bindwijze:gebonden
Uitgever:Springer Nature Singapore

Inhoudsopgave

<div>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.</div>
€ 144,99
Levertijd ongeveer 8 werkdagen

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        Advances in Principal Component Analysis