Advances in Principal Component Analysis

Advances in Principal Component Analysis

Research and Development

Naik, Ganesh R.

Springer Verlag, Singapore

02/2018

252

Dura

Inglês

9789811067037

15 a 20 dias

657


ebook

Descrição não disponível.
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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Principal Component Analysis (PCA);Source separation;Source identification;Dimensionality reduction;Nonlinear PCA;Kernel PCA;Sparse PCA;Time-frequency signal;Pattern recognition