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Independent Component Analysis.

Seungjin Choi
- pp 435-459
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TLDR
The standardization of the IC model is talked about, and on the basis of n independent copies of x, the aim is to find an estimate of an unmixing matrix Γ such that Γx has independent components.
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The article was published on 2012-01-01 and is currently open access. It has received 2296 citations till now. The article focuses on the topics: Independent component analysis.

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Citations
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Redundancy as a Graph-Based Index of Frequency Specific MEG Functional Connectivity

TL;DR: The redundancy in the MEG networks, for each frequency band, was significantly higher than in the random graphs, thus, confirming a natural tendency of the brain to present multiple interaction pathways between different specialized areas.
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A Review of Feature Extraction Software for Microarray Gene Expression Data

TL;DR: This paper reviews numerous software applications that can be used for feature extraction, mainly for Principal Component Analysis (PCA), Independent Component analysis (ICA), Partial Least Squares (PLS), and Local Linear Embedding (LLE).
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Different mechanisms are responsible for dishabituation of electrophysiological auditory responses to a change in acoustic identity than to a change in stimulus location

TL;DR: The finding that habituation occurs to repeated exposure to the same song and dishabituation with a novel song, similar to that described in head-fixed, restrained animals, suggests that neuronal memories of the acoustic identity and spatial location are different, and that allocentric location of a stimulus is not encoded as part of the memory for an auditory object, while its acoustic properties are.
Posted Content

Locality Preserving Projections for Grassmann manifold

TL;DR: Wang et al. as mentioned in this paper proposed an unsupervised dimensionality reduction algorithm on Grassmann manifold based on the Locality Preserving Projections (LPP) criterion, which aims to preserve local structure of data in the dimension-reduced space.
References
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Book

Elements of information theory

TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
Book

Matrix computations

Gene H. Golub
Book

Introduction to Statistical Pattern Recognition

TL;DR: This completely revised second edition presents an introduction to statistical pattern recognition, which is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field.
Journal ArticleDOI

An information-maximization approach to blind separation and blind deconvolution

TL;DR: It is suggested that information maximization provides a unifying framework for problems in "blind" signal processing and dependencies of information transfer on time delays are derived.
Journal ArticleDOI

Independent component analysis, a new concept?

Pierre Comon
- 01 Apr 1994 - 
TL;DR: An efficient algorithm is proposed, which allows the computation of the ICA of a data matrix within a polynomial time and may actually be seen as an extension of the principal component analysis (PCA).