Systematically explores the relationship between principal component analysis (PCA) and neural networks. Provides a synergistic examination of the mathematical,

Principal component analysis is probably the oldest and best known of the It was first introduced by Pearson (1901), techniques ofmultivariate analysis. and dev

The book starts with the quote of the classical Pearson definition of PCA and includes reviews of various methods: NLPCA, ICA, MDS, embedding and clustering alg

Content Description #Includes bibliographical references and index.

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 e