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Language: en
Pages: 339
Pages: 339
Type: BOOK - Published: 2017-01-09 - Publisher: Springer
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
Language: en
Pages: 282
Pages: 282
Type: BOOK - Published: 1996-03-08 - Publisher: Wiley-Interscience
Systematically explores the relationship between principal component analysis (PCA) and neural networks. Provides a synergistic examination of the mathematical,
Language: en
Pages: 590
Pages: 590
Type: BOOK - Published: 2016-04-11 - Publisher: Springer
This book provides a comprehensive introduction to the latest advances in the mathematical theory and computational tools for modeling high-dimensional data dra
Language: en
Pages: 283
Pages: 283
Type: BOOK - Published: 2013-03-09 - Publisher: Springer Science & Business Media
Principal component analysis is probably the oldest and best known of the It was first introduced by Pearson (1901), techniques ofmultivariate analysis. and dev
Language: en
Pages: 361
Pages: 361
Type: BOOK - Published: 2007-10 - Publisher: Springer Science & Business Media
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