Store besparelser
Hurtig levering
Gemte
Log ind
0
Kurv
Kurv

Nonlinear Blind Source Separation and Blind Mixture Identification

- Methods for Bilinear, Linear-quadratic and Polynomial Mixtures

Nonlinear Blind Source Separation and Blind Mixture Identification

- Methods for Bilinear, Linear-quadratic and Polynomial Mixtures
Tjek vores konkurrenters priser
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 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.

Tjek vores konkurrenters priser
Normalpris
kr 478
Fragt: 39 kr
6 - 8 hverdage
20 kr
Pakkegebyr
God 4 anmeldelser på
Tjek vores konkurrenters priser
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 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.

Produktdetaljer
Sprog: Engelsk
Sider: 71
ISBN-13: 9783030649760
Indbinding: Paperback
Udgave:
ISBN-10: 3030649768
Kategori: Numerisk analyse
Udg. Dato: 3 feb 2021
Længde: 0mm
Bredde: 155mm
Højde: 235mm
Forlag: Springer Nature Switzerland AG
Oplagsdato: 3 feb 2021
Forfatter(e) Shahram Hosseini, Leonardo Tomazeli Duarte, Yannick Deville


Kategori Numerisk analyse


ISBN-13 9783030649760


Sprog Engelsk


Indbinding Paperback


Sider 71


Udgave


Længde 0mm


Bredde 155mm


Højde 235mm


Udg. Dato 3 feb 2021


Oplagsdato 3 feb 2021


Forlag Springer Nature Switzerland AG

Vi anbefaler også
Kategori sammenhænge