Advances in Principal Component Analysis
Research and Development
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Beschreibung
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.
Covers the latest, cutting-edge topics in PCA, with a focus on open problems
Balances theory and applications, with concrete examples
Offers in-depth analysis of PCA topics simply not covered anywhere else
Includes the most advanced and popular areas of PCA, offering a broad and comprehensive description of all the core principles
Covers the latest, cutting-edge topics in PCA, with a focus on open problems Balances theory and applications, with concrete examples Offers in-depth analysis of PCA topics simply not covered anywhere else Includes the most advanced and popular areas of PCA, offering a broad and comprehensive description of all the core principles
Autor*in
Ganesh R. Naik
Themen in »Advances in Principal Component Analysis«
Principal Component Analysis (PCA) Source separation Source identification Dimensionality reduction Nonlinear PCA Kernel PCA Sparse PCA Time-frequency signal Pattern recognition