Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-Way Data Analysis and Blind Source Separation

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9780470746660: Nonnegative Matrix and Tensor Factorizations: Applications to Exploratory Multi-Way Data Analysis and Blind Source Separation

This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF's various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Decompositions (NTD). NMF/NTF and their extensions are increasingly used as tools in signal and image processing, and data analysis, having garnered interest due to their capability to provide new insights and relevant information about the complex latent relationships in experimental data sets. It is suggested that NMF can provide meaningful components with physical interpretations; for example, in bioinformatics, NMF and its extensions have been successfully applied to gene expression, sequence analysis, the functional characterization of genes, clustering and text mining. As such, the authors focus on the algorithms that are most useful in practice, looking at the fastest, most robust, and suitable for large-scale models. Key features:* Acts as a single source reference guide to NMF, collating information that is widely dispersed in current literature, including the authors' own recently developed techniques in the subject area.* Uses generalized cost functions such as Bregman, Alpha and Beta divergences, to present practical implementations of several types of robust algorithms, in particular Multiplicative, Alternating Least Squares, Projected Gradient and Quasi Newton algorithms.* Provides a comparative analysis of the different methods in order to identify approximation error and complexity.* Includes pseudo codes and optimized MATLAB source codes for almost all algorithms presented in the book. The increasing interest in nonnegative matrix and tensor factorizations, as well as decompositions and sparse representation of data, will ensure that this book is essential reading for engineers, scientists, researchers, industry practitioners and graduate students across signal and image processing; neuroscience; data mining and data analysis; computer science; bioinformatics; speech processing; biomedical engineering; and multimedia.

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Andrzej Cichocki, Shun-Ichi Amari, Rafal Zdunek
Editore: John Wiley and Sons Ltd, United States (2009)
ISBN 10: 0470746661 ISBN 13: 9780470746660
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Descrizione libro John Wiley and Sons Ltd, United States, 2009. Hardback. Condizione libro: New. 250 x 176 mm. Language: English . Brand New Book. This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF s various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Decompositions (NTD). NMF/NTF and their extensions are increasingly used as tools in signal and image processing, and data analysis, having garnered interest due to their capability to provide new insights and relevant information about the complex latent relationships in experimental data sets. It is suggested that NMF can provide meaningful components with physical interpretations; for example, in bioinformatics, NMF and its extensions have been successfully applied to gene expression, sequence analysis, the functional characterization of genes, clustering and text mining. As such, the authors focus on the algorithms that are most useful in practice, looking at the fastest, most robust, and suitable for large-scale models. Key features:* Acts as a single source reference guide to NMF, collating information that is widely dispersed in current literature, including the authors own recently developed techniques in the subject area.* Uses generalized cost functions such as Bregman, Alpha and Beta divergences, to present practical implementations of several types of robust algorithms, in particular Multiplicative, Alternating Least Squares, Projected Gradient and Quasi Newton algorithms.* Provides a comparative analysis of the different methods in order to identify approximation error and complexity.* Includes pseudo codes and optimized MATLAB source codes for almost all algorithms presented in the book. The increasing interest in nonnegative matrix and tensor factorizations, as well as decompositions and sparse representation of data, will ensure that this book is essential reading for engineers, scientists, researchers, industry practitioners and graduate students across signal and image processing; neuroscience; data mining and data analysis; computer science; bioinformatics; speech processing; biomedical engineering; and multimedia. Codice libro della libreria AAH9780470746660

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Andrzej Cichocki, Shun-Ichi Amari, Rafal Zdunek
Editore: John Wiley and Sons Ltd, United States (2009)
ISBN 10: 0470746661 ISBN 13: 9780470746660
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Descrizione libro John Wiley and Sons Ltd, United States, 2009. Hardback. Condizione libro: New. 250 x 176 mm. Language: English . Brand New Book. This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF s various extensions and modifications, especially Nonnegative Tensor Factorizations (NTF) and Nonnegative Tucker Decompositions (NTD). NMF/NTF and their extensions are increasingly used as tools in signal and image processing, and data analysis, having garnered interest due to their capability to provide new insights and relevant information about the complex latent relationships in experimental data sets. It is suggested that NMF can provide meaningful components with physical interpretations; for example, in bioinformatics, NMF and its extensions have been successfully applied to gene expression, sequence analysis, the functional characterization of genes, clustering and text mining. As such, the authors focus on the algorithms that are most useful in practice, looking at the fastest, most robust, and suitable for large-scale models. Key features:* Acts as a single source reference guide to NMF, collating information that is widely dispersed in current literature, including the authors own recently developed techniques in the subject area.* Uses generalized cost functions such as Bregman, Alpha and Beta divergences, to present practical implementations of several types of robust algorithms, in particular Multiplicative, Alternating Least Squares, Projected Gradient and Quasi Newton algorithms.* Provides a comparative analysis of the different methods in order to identify approximation error and complexity.* Includes pseudo codes and optimized MATLAB source codes for almost all algorithms presented in the book. The increasing interest in nonnegative matrix and tensor factorizations, as well as decompositions and sparse representation of data, will ensure that this book is essential reading for engineers, scientists, researchers, industry practitioners and graduate students across signal and image processing; neuroscience; data mining and data analysis; computer science; bioinformatics; speech processing; biomedical engineering; and multimedia. Codice libro della libreria AAH9780470746660

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Andrzej Cichocki
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Descrizione libro Wileyand#8211;Blackwell, 2009. HRD. Condizione libro: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Codice libro della libreria FW-9780470746660

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Cichocki, Andrzej
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Descrizione libro John Wiley & Sons, 2016. Paperback. Condizione libro: New. PRINT ON DEMAND Book; New; Publication Year 2016; Not Signed; Fast Shipping from the UK. No. book. Codice libro della libreria ria9780470746660_lsuk

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Descrizione libro 2009. Hardcover. Condizione libro: New. 1st. 174mm x 247mm x 29mm. Hardcover. This book provides a broad survey of models and efficient algorithms for Nonnegative Matrix Factorization (NMF). This includes NMF's various extensions and modifications, especially Nonneg.Shipping may be from multiple locations in the US or from the UK, depending on stock availability. 500 pages. 1.204. Codice libro della libreria 9780470746660

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Cichocki, Andrzej; Zdunek, Rafal; Phan, Anh Huy; Amari, Shun-ichi
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Descrizione libro Wiley, 2009. Hardcover. Condizione libro: New. book. Codice libro della libreria 0470746661

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Andrzej Cichocki
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Descrizione libro Wileyand#8211;Blackwell, 2009. HRD. Condizione libro: New. New Book.Shipped from US within 10 to 14 business days.THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice libro della libreria IP-9780470746660

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Cichocki, Andrzej, Zdunek, Rafal, Phan,
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Descrizione libro Wiley, 2017. Hardcover. Condizione libro: New. This item is printed on demand. Codice libro della libreria P110470746661

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ANDRZEJ CICHOCKI
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Descrizione libro 2009. Hardback. Condizione libro: NEW. 9780470746660 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. Codice libro della libreria HTANDREE0773112

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Cichocki, Andrzej/ Zdunek, Rafal/ Phan, Anh Huy/ Amari, Shun-Ichi
Editore: John Wiley & Sons Inc (2009)
ISBN 10: 0470746661 ISBN 13: 9780470746660
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Descrizione libro John Wiley & Sons Inc, 2009. Hardcover. Condizione libro: Brand New. 1st edition. 500 pages. 9.84x6.93x1.18 inches. In Stock. Codice libro della libreria __0470746661

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