Advances in Principal Component Analysis Research and Development
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 man...
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| Format: | eBook |
| Language: | English |
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Singapore
Springer Nature Singapore
2018, 2018
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| Edition: | 1st ed. 2018 |
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| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- 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