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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Naik, Ganesh R. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2018.
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.