Independent Component Analysis

Independent Component Analysis
Author :
Publisher : MIT Press
Total Pages : 224
Release :
ISBN-10 : 0262693151
ISBN-13 : 9780262693158
Rating : 4/5 (51 Downloads)

Book Synopsis Independent Component Analysis by : James V. Stone

Download or read book Independent Component Analysis written by James V. Stone and published by MIT Press. This book was released on 2004 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors. For reasons of computational and conceptual simplicity, the representation is often sought as a linear transformation of the original data. In other words, each component of the representation is a linear combination of the original variables. Well-known linear transformation methods include principal component analysis, factor analysis, and projection pursuit. Independent component analysis (ICA) is a recently developed method in which the goal is to find a linear representation of nongaussian data so that the components are statistically independent, or as independent as possible. Such a representation seems to capture the essential structure of the data in many applications, including feature extraction and signal separation.


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