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
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245 1 0 |a Advances in Principal Component Analysis  |h [electronic resource] :  |b Research and Development /  |c edited by Ganesh R. Naik. 
250 |a 1st ed. 2018. 
264 1 |a Singapore :  |b Springer Singapore :  |b Imprint: Springer,  |c 2018. 
300 |a VII, 252 p. 94 illus., 75 illus. in color.  |b online resource. 
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505 0 |a 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. 
520 |a 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 many scientific journals papers worldwide, the book presents them in a methodologically unified form. Offering vital insights into the subject matter in self-contained chapters that balance the theory and concrete applications, and especially focusing on open problems, it is essential reading for all researchers and practitioners with an interest in PCA. 
650 0 |a Signal processing. 
650 0 |a Image processing. 
650 0 |a Speech processing systems. 
650 0 |a Pattern recognition. 
650 0 |a Computational intelligence. 
650 0 |a Computer mathematics. 
650 0 |a Biomedical engineering. 
650 1 4 |a Signal, Image and Speech Processing.  |0 http://scigraph.springernature.com/things/product-market-codes/T24051 
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650 2 4 |a Computational Intelligence.  |0 http://scigraph.springernature.com/things/product-market-codes/T11014 
650 2 4 |a Computational Mathematics and Numerical Analysis.  |0 http://scigraph.springernature.com/things/product-market-codes/M1400X 
650 2 4 |a Biomedical Engineering and Bioengineering.  |0 http://scigraph.springernature.com/things/product-market-codes/T2700X 
700 1 |a Naik, Ganesh R.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
710 2 |a SpringerLink (Online service) 
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