Format:
1 Online-Ressource (114 Seiten)
Edition:
Also available in print
ISBN:
1598290312
,
9781598290318
Series Statement:
Synthesis Lectures on Signal Processing #2
Content:
The purpose of this lecture book is to present the state of the art in nonlinear blind source separation, in a form appropriate for students, researchers and developers. Source separation deals with the problem of recovering sources that are observed in a mixed condition. When we have little knowledge about the sources and about the mixture process, we speak of blind source separation. Linear blind source separation is a relatively well studied subject. Nonlinear blind source separation is still in a less advanced stage, but has seen several significant developments in the last few years. This publication reviews the main nonlinear separation methods, including the separation of post-nonlinear mixtures, and the MISEP, ensemble learning and kTDSEP methods for generic mixtures. These methods are studied with a significant depth. A historical overview is also presented, mentioning most of the relevant results, on nonlinear blind source separation, that have been presented over the years
Content:
The purpose of this lecture book is to present the state of the art in nonlinear blind source separation, in a form appropriate for students, researchers and developers. Source separation deals with the problem of recovering sources that are observed in a mixed condition. When we have little knowledge about the sources and about the mixture process, we speak of blind source separation. Linear blind source separation is a relatively well studied subject. Nonlinear blind source separation is still in a less advanced stage, but has seen several significant developments in the last few years. This publication reviews the main nonlinear separation methods, including the separation of post-nonlinear mixtures, and the MISEP, ensemble learning and kTDSEP methods for generic mixtures. These methods are studied with a significant depth. A historical overview is also presented, mentioning most of the relevant results, on nonlinear blind source separation, that have been presented over the years
Content:
Acknowledgments -- Notation -- Preface -- 1. Introduction. -- 1.1. Basic concepts -- 1.2. Summary -- 2. Linear source separation -- 2.1. Statement of the problem -- 2.2. INFOMAX -- 2.3. Exploiting the time-domain structure -- 2.4. Other methods : JADE and FastICA -- 2.5. Summary -- 3. Nonlinear separation -- 3.1. Post-nonlinear mixtures -- 3.2. Unconstrained nonlinear separation -- 3.3. Conclusion -- 4. Final comments -- A. Statistical concepts -- A.1. Passing a random variable through its cumulative distribution function -- A.2. Entropy -- A.3. Kullback-Leibler divergence -- A.4. Mutual information -- B. Online software and data
Note:
Description based upon print version of record
,
1. Introduction.1.1. Basic concepts -- 1.2. Summary -- 2. Linear source separation -- 2.1. Statement of the problem -- 2.2. INFOMAX -- 2.3. Exploiting the time-domain structure -- 2.4. Other methods : JADE and FastICA -- 2.5. Summary -- 3. Nonlinear separation -- 3.1. Post-nonlinear mixtures -- 3.2. Unconstrained nonlinear separation -- 3.3. Conclusion -- 4. Final comments -- A. Statistical concepts -- A.1. Passing a random variable through its cumulative distribution function -- A.2. Entropy -- A.3. Kullback-Leibler divergence -- A.4. Mutual information -- B. Online software and data.
,
Also available in print.
,
System requirements: Adobe Acrobat Reader.
,
Mode of access: World Wide Web.
Additional Edition:
ISBN 1598290304
Additional Edition:
ISBN 9781598290301
Additional Edition:
Erscheint auch als Druck-Ausgabe Nonlinear Source Separation
Language:
English
Keywords:
Electronic books
DOI:
10.2200/S00016ED1V01Y200602SPR002
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