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Blind Source Separation Dependent Component Analysis /

This book provides readers a complete and self-contained set of knowledge about dependent source separation, including the latest development in this field. The book gives an overview on blind source separation where three promising blind separation techniques that can tackle mutually correlated sou...

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Main Authors: Xiang, Yong. (Author, http://id.loc.gov/vocabulary/relators/aut), Peng, Dezhong. (http://id.loc.gov/vocabulary/relators/aut), Yang, Zuyuan. (http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Language:English
Published: Singapore : Springer Singapore : Imprint: Springer, 2015.
Edition:1st ed. 2015.
Series:SpringerBriefs in Signal Processing,
Subjects:
Signal processing.
Image processing.
Speech processing systems.
Electrical engineering.
Electronic circuits.
Signal, Image and Speech Processing.
Communications Engineering, Networks.
Circuits and Systems.
Online Access:https://doi.org/10.1007/978-981-287-227-2
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505 0 |a Introduction -- DCA Exploiting Nonnegativity -- DCA Utilizing Time-Frequency Analysis (TFA) -- DCA Employing Precoding -- Summary and Future Work. 
520 |a This book provides readers a complete and self-contained set of knowledge about dependent source separation, including the latest development in this field. The book gives an overview on blind source separation where three promising blind separation techniques that can tackle mutually correlated sources are presented. The book further focuses on the non-negativity based methods, the time-frequency analysis based methods, and the pre-coding based methods, respectively. 
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