Principal Component Analysis Networks and Algorithms

This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc. It also discusses in detail various a...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Kong, Xiangyu (Συγγραφέας), Hu, Changhua (Συγγραφέας), Duan, Zhansheng (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2017.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Introduction
  • Eigenvalue and singular value decomposition
  • Principal component analysis neural networks
  • Minor component analysis neural networks
  • Dual purpose methods for principal and minor component analysis
  • Deterministic discrete time system for PCA or MCA methods
  • Generalized feature extraction method
  • Coupled principal component analysis
  • Singular feature extraction neural networks.