ISBN: 9780521792981 - independent component analysis: principles and practice (10 Ergebnisse)

Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,750grams, ISBN:9780521792981. …

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: New. pp. 352 Figures, Illus.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Zustand: As New. Unread book in perfect condition.

Zustand: New. In English.

Hardcover. Zustand: Brand New. 1st edition. 338 pages. 9.00x6.25x1.00 inches. In Stock.

Zustand: New. 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 applicatio.

Zustand: New. Series of edited papers on Independent Component Analysis, containing theory and applications. Editor(s): Roberts, Stephen; Everson, Richard. Num Pages: 352 pages, 99 figures. BIC Classification: PBT; TJK. Category: (P) Professional & Vocational. Dimension: 228 x 152 x 24. Weight in Grams: 700. . 2001. Hardback. . . . . Books ship from the US and Ireland.…

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…