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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Detaylı Bibliyografya
Müşterek Yazar: SpringerLink (Online service)
Diğer Yazarlar: Naik, Ganesh R. (Editör)
Materyal Türü: e-Kitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Singapore : Springer Nature Singapore : 2018.
Imprint: Springer,
Edisyon:1st ed. 2018.
Konular:
Signal processing.
Pattern recognition systems.
Computational intelligence.
Mathematics > Data processing.
Biomedical engineering.
Signal, Speech and Image Processing .
Automated Pattern Recognition.
Computational Intelligence.
Computational Mathematics and Numerical Analysis.
Biomedical Engineering and Bioengineering.
Online Erişim:Full-text access
İçindekiler:
  • 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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