Nonlinear Blind Source Separation by Deville Yannick (19 results)
Nonlinear Blind Source Separation and Blind Mixture Identification : Methods for Bilinear, Linear-quadratic and Polynomial Mixtures
Deville, Yannick; Duarte, Leonardo Tomazeli; Hosseini, Shahram
Language: English
Published by Springer, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
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Nonlinear Blind Source Separation and Blind Mixture Identification: Methods for Bilinear, Linear-quadratic and Polynomial Mixtures (SpringerBriefs in Electrical and Computer Engineering)
Deville, Yannick; Duarte, Leonardo Tomazeli; Hosseini, Shahram
Language: English
Published by Springer, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
- Softcover
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Nonlinear Blind Source Separation and Blind Mixture Identification : Methods for Bilinear, Linear-quadratic and Polynomial Mixtures
Deville, Yannick; Duarte, Leonardo Tomazeli; Hosseini, Shahram
Language: English
Published by Springer, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
- Softcover
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Nonlinear Blind Source Separation and Blind Mixture Identification: Methods for Bilinear, Linear-quadratic and Polynomial Mixtures (SpringerBriefs in Electrical and Computer Engineering)
Deville, Yannick; Duarte, Leonardo Tomazeli; Hosseini, Shahram
Language: English
Published by Springer, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
- Softcover
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Language: English
Published by Springer 2021-02-03, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
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Nonlinear Blind Source Separation and Blind Mixture Identification : Methods for Bilinear, Linear-quadratic and Polynomial Mixtures
Deville, Yannick; Duarte, Leonardo Tomazeli; Hosseini, Shahram
Language: English
Published by Springer, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
- Softcover
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Language: English
Published by Springer, 2021
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Nonlinear Blind Source Separation and Blind Mixture Identification : Methods for Bilinear, Linear-quadratic and Polynomial Mixtures
Deville, Yannick; Duarte, Leonardo Tomazeli; Hosseini, Shahram
Language: English
Published by Springer, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
- Softcover
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Nonlinear Blind Source Separation and Blind Mixture Identification: Methods for Bilinear, Linear-quadratic and Polynomial Mixtures (SpringerBriefs in Electrical and Computer Engineering)
Deville, Yannick; Duarte, Leonardo Tomazeli; Hosseini, Shahram
Language: English
Published by Springer, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
- Softcover
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Nonlinear Blind Source Separation and Blind Mixture Identification: Methods for Bilinear, Linear-quadratic and Polynomial Mixtures
Deville, Yannick/ Duarte, Leonardo Tomazeli/ Hosseini, Shahram
Language: English
Published by Springer Nature, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
- Softcover
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Language: English
Published by Springer, 2021
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- Softcover
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Language: English
Published by Springer International Publishing, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
- Softcover
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a detailed survey of the methods that were recently developed to handle advanced versions of the blind source separation problem, which involve several types of nonlinear mixtures. Another attractive feature of the book is that i…t is based on a coherent framework. More precisely, the authors first present a general procedure for developing blind source separation methods. Then, all reported methods are defined with respect to this procedure. This allows the reader not only to more easily follow the description of each method but also to see how these methods relate to one another. The coherence of this book also results from the fact that the same notations are used throughout the chapters for the quantities (source signals and so on) that are used in various methods. Finally, among the quite varied types of processing methods that are presented in this book, a significant part of this description is dedicated to methods based on artificial neural networks, especially recurrent ones, which are currently of high interest to the data analysis and machine learning community in general, beyond the more specific signal processing and blind source separation communities.
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Published by Springer, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
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Taschenbuch. Condition: Neu. Nonlinear Blind Source Separation and Blind Mixture Identification | Methods for Bilinear, Linear-quadratic and Polynomial Mixtures | Yannick Deville (u. a.) | Taschenbuch | SpringerBriefs in Electrical and Computer Engineering | ix | Englisch | 2021 | Springer | EAN 9783030649760 | Verantwortliche P…erson für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Language: English
Published by Springer, 2021
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Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer International Publishing Feb 2021, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a detailed survey of the methods that were recently developed to handle advanced versions of the blind source separation problem, which involve several types of nonlinear mixtures. Another attractive feature of th…e book is that it is based on a coherent framework. More precisely, the authors first present a general procedure for developing blind source separation methods. Then, all reported methods are defined with respect to this procedure. This allows the reader not only to more easily follow the description of each method but also to see how these methods relate to one another. The coherence of this book also results from the fact that the same notations are used throughout the chapters for the quantities (source signals and so on) that are used in various methods. Finally, among the quite varied types of processing methods that are presented in this book, a significant part of this description is dedicated to methods based on artificial neural networks, especially recurrent ones, which are currently of high interest to the data analysis and machine learning community in general, beyond the more specific signal processing and blind source separation communities. 84 pp. Englisch.
Nonlinear Blind Source Separation and Blind Mixture Identification: Methods for Bilinear, Linear-quadratic and Polynomial Mixtures (SpringerBriefs in Electrical and Computer Engineering)
Deville, Yannick; Duarte, Leonardo Tomazeli; Hosseini, Shahram
Language: English
Published by Springer, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
- Softcover
- Print on Demand
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Nonlinear Blind Source Separation and Blind Mixture Identification: Methods for Bilinear, Linear-quadratic and Polynomial Mixtures (SpringerBriefs in Electrical and Computer Engineering)
Deville, Yannick; Duarte, Leonardo Tomazeli; Hosseini, Shahram
Language: English
Published by Springer, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
- Softcover
- Print on Demand
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Published by Springer International Publishing, 2021
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents advanced configurations of the blind source separation problem, involving bilinear, linear-quadratic and polynomial mixing modelsProvides a detailed and coherent description of the methods reported in the lit…erature for handling these typ.
Language: English
Published by Springer, Springer Feb 2021, 2021
Series: SpringerBriefs in Electrical and Computer Engineering, Book 205 of 209. Book 205 of 209 - SpringerBriefs in Electrical and Computer Engineering
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a detailed survey of the methods that were recently developed to handle advanced versions of the blind source separation problem, which involve several types of nonlinear mixtures. Another attractive feature of the bo…ok is that it is based on a coherent framework. More precisely, the authors first present a general procedure for developing blind source separation methods. Then, all reported methods are defined with respect to this procedure. This allows the reader not only to more easily follow the description of each method but also to see how these methods relate to one another. The coherence of this book also results from the fact that the same notations are used throughout the chapters for the quantities (source signals and so on) that are used in various methods. Finally, among the quite varied types of processing methods that are presented in this book, a significant part of this description is dedicated to methods based on artificial neural networks, especially recurrent ones, which are currently of high interest to the data analysis and machine learning community in general, beyond the more specific signal processing and blind source separation communities.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 84 pp. Englisch.
