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...
Συγγραφή απο Οργανισμό/Αρχή: | |
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Άλλοι συγγραφείς: | |
Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
Γλώσσα: | English |
Έκδοση: |
Singapore :
Springer Singapore : Imprint: Springer,
2018.
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Έκδοση: | 1st ed. 2018. |
Θέματα: | |
Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 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.