Nonlinear Blind Source Separation and Blind Mixture Identification - Methods for Bilinear, Linear-quadratic and Polynomial Mixtures (Paperback, 1st ed. 2021)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Electrical and Computer Engineering
Release date:	February 2021
First published:	2021
Authors:	Yannick Deville • Leonardo Tomazeli Duarte • Shahram Hosseini
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	71
Edition:	1st ed. 2021
ISBN-13:	978-3-03-064976-0
Categories:	Books > Science & Mathematics > Mathematics > Numerical analysis Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General Promotions
LSN:	3-03-064976-8
Barcode:	9783030649760

Is the information for this product incomplete, wrong or inappropriate? Let us know about it.

Does this product have an incorrect or missing image? Send us a new image.

Is this product missing categories? Add more categories.

Review This Product

No reviews yet - be the first to create one!