Nonlinear Source Separation
Almeida, L. B.
Nonlinear Source Separation by Luis Almeida - 1st edition 2006 - 1 recurso en línea (XII, 101 páginas) - Synthesis Lectures on Signal Processing 1932-1694 .
Introduction -- Linear Source Separation -- Nonlinear Separation -- Final Comments -- Statistical Concepts -- Online Software and Data.
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, however 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.
9783031025266
10.1007/978-3-031-02526-6 doi
Sistemas no lineales
Proceso de señales
TK5102.9 / 2006 EB
Nonlinear Source Separation by Luis Almeida - 1st edition 2006 - 1 recurso en línea (XII, 101 páginas) - Synthesis Lectures on Signal Processing 1932-1694 .
Introduction -- Linear Source Separation -- Nonlinear Separation -- Final Comments -- Statistical Concepts -- Online Software and Data.
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, however 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.
9783031025266
10.1007/978-3-031-02526-6 doi
Sistemas no lineales
Proceso de señales
TK5102.9 / 2006 EB