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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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Journal ArticleDOI

DCT-Based Preprocessing Approach for ICA in Hyperspectral Data Analysis.

TL;DR: Experimental results in both instances indicate that data after the proposed DCT preprocessing method combined with ICA yields superior hyperspectral classification accuracy.
Journal ArticleDOI

Independent vector analysis based on overlapped cliques of variable width for frequency-domain blind signal separation

TL;DR: A novel method is proposed to improve the performance of independent vector analysis (IVA) for blind signal separation of acoustic mixtures by allowing variable amounts of statistical dependencies according to the correlation coefficients observed in real acoustic signals and, hence, enables more accurate modeling of statistical dependency.
Journal ArticleDOI

Unifying perceptual and behavioral learning with a correlative subspace learning rule

TL;DR: The proposed subspace learning algorithm allows to integrate both learning systems and to smoothly change form perceptual learning only to behavioral learning only, and shows that in a robot open area foraging task an active adaptation of the balance between perceptual and behavioral learning is necessary in order to stabilize the performance of the robot.
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A Generalized Directional Laplacian Distribution : Estimation, Mixture Models and Audio Source Separation

TL;DR: The author explores the application of the derived DLD mixture model to cluster sound sources that exist in an underdetermined instantaneous sound mixture, offering a fast and stable solution.
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Jointly optimal denoising, dereverberation, and source separation

TL;DR: Methods that can optimize a Convolutional BeamFormer (CBF) for jointly performing denoising, dereverberation, and source separation (DN+DR+SS) in a computationally efficient way are proposed.
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).