Independent Component Analysis is popular PDF and ePub book, written by James V. Stone in 2004, it is a fantastic choice for those who relish reading online the Independent component analysis genre. Let's immerse ourselves in this engaging Independent component analysis book by exploring the summary and details provided below. Remember, Independent Component Analysis can be Read Online from any device for your convenience.
Independent Component Analysis Book PDF Summary
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.
Detail Book of Independent Component Analysis PDF
- Author : James V. Stone
- Release : 30 September 2024
- Publisher : MIT Press
- ISBN : 0262693151
- Genre : Independent component analysis
- Total Page : 224 pages
- Language : English
- PDF File Size : 9,9 Mb
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