Independent Component Analysis by Stephen Roberts

Independent Component Analysis by Stephen Roberts

Independent Component Analysis (ICA) has recently become an important tool for modelling and understanding empirical datasets. It is a method of separating out independent sources from linearly mixed data, and belongs to the class of general linear models. ICA provides a better decomposition than other well-known models such as principal component analysis. This self-contained book contains a structured series of edited papers by leading researchers in the field, including an extensive introduction to ICA. The major theoretical bases are reviewed from a modern perspective, current developments are surveyed and many case studies of applications are described in detail. The latter include biomedical examples, signal and image denoising and mobile communications. ICA is discussed in the framework of general linear models, but also in comparison with other paradigms such as neural network and graphical modelling methods. The book is ideal for researchers and graduate students in the field.

'The book is intended to be a self-contained introduction and overview of this important development and it appears to meet the requirement admirably' Alex M. Andrew, Robotica
'… is ideal for graduate students and researchers in the field.' Zentralblatt MATH

Roberts, Stephen: - Stephen Roberts is associate professor and reader in modern Spanish literature and intellectual history at the University of Nottingham. He has published widely on the literature and thought of Spain between the 1890s and 1936, as well as on the figure of the intellectual in Spain.

SKU	Non disponible
ISBN 13	9780521792981
ISBN 10	0521792983
Titre	Independent Component Analysis
Auteur	Stephen Roberts
État	Non disponible
Type de reliure	Hardback
Éditeur	Cambridge University Press
Année de publication	2001-03-01
Nombre de pages	352
Note de couverture	La photo du livre est présentée à titre d'illustration uniquement. La reliure, la couverture ou l'édition réelle peuvent varier.
Note	Non disponible