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Hardcover. 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. Independent Component Analysis is an important tool for modelling and understanding empirical datasets consisting of mixtures of independent sources. This book contains papers by leading researchers on the subject. The theory is reviewed and many applications are described. Ideal for researchers and graduate students in the field. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780521792981
Series of edited papers on Independent Component Analysis, containing theory and applications.
Review:
'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
Title: Independent Component Analysis (Hardcover)
Publisher: Cambridge University Press, Cambridge
Publication Date: 2001
Binding: Hardcover
Condition: new
Edition: 1st Edition
Seller: CitiRetail, Stevenage, United Kingdom
Hardcover. Condition: new. Hardcover. 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. Independent Component Analysis is an important tool for modelling and understanding empirical datasets consisting of mixtures of independent sources. This book contains papers by leading researchers on the subject. The theory is reviewed and many applications are described. Ideal for researchers and graduate students in the field. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780521792981
Quantity: 1 available