Independent Component Analysis

Independent Component Analysis (2001)

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by Aapo Hyvärinen

Venue:	Neural Computing Surveys
Citations:	1325 - 89 self

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@ARTICLE{Hyvärinen01independentcomponent,
    author = {Aapo Hyvärinen},
    title = {Independent Component Analysis},
    journal = {Neural Computing Surveys},
    year = {2001},
    volume = {2}
}

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Abstract

A common problem encountered in such disciplines as statistics, data analysis, signal processing, and neural network research, is nding a suitable representation of multivariate data. For computational and conceptual simplicity, such a representation is often sought as a linear transformation of the original data. Well-known linear transformation methods include, for example, principal component analysis, factor analysis, and projection pursuit. A recently developed linear transformation method is independent component analysis (ICA), in which the desired representation is the one that minimizes the statistical dependence of the components of the representation. Such a representation seems to capture the essential structure of the data in many applications. In this paper, we survey the existing theory and methods for ICA. 1

Citations

3034	Self-organizing Maps - Kohonen - 1997
2166	A Theory for Multiresolution Signal Decomposition: The Wavelet Representation - MALLAT - 1989
1659	Robust Statistics - Huber - 1981
1254	Independent Component Analysis, a new concept - Comon
1065	Adaptive filter theory - Haykin - 1991
1001	An information-maximization approach to blind separation and blind deconvolution - Bell, Sejnowski - 1995
852	Emergence of simple-cell receptive field properties by learning a sparse code for natural images - Olshausen, Field - 1996
543	Sparse coding with an overcomplete basis set: a strategy employed by V1 - Sankaranarayanan, Olshausen, et al. - 1997
499	Probability and statistics - DeGroot, Schervish - 2011
469	Fast and robust fixed-point algorithms for independent component analysis - Hyvarinen - 1999
453	Blind Beamforming for non-Gaussian Signals - Cardoso, Souloumiac
443	The ''independent components'' of natural scenes are edge filters - Bell, Sejnowski - 1997
411	Blind separation of sources, Part I: An adaptive algorithm based on neuromimetic architecture - Jutten, Herault - 1993
397	A Fast Fixed-Point Algorithm for Independent Component Analysis, Neural Computation - Hyvarinen, Oja - 1997
387	A simplified neuron model as a principal component analyzer - Oja - 1982
367	Equivariant adaptative source separation - Cardoso, Laheld - 1996
353	What is the goal of sensory coding - Field - 1994
342	signal separation: statistical principles - Cardoso, Blind - 1998
305	Possible principles underlying the transformation of sensory messages. Sensory communication 217–234 - Barlow - 1961
272	Principal curves - Hastie, Stuetzle - 1989
262	The Generative Topographic Mapping - Bishop, Svensén, et al. - 1998
258	Independent component filters of natural images compared with simple cells in the primary visual cortex - Hateren, Schaaf - 1998
232	Normalization of cell responses in cat striate cortex - Heeger - 1992
232	Learning Overcomplete Representations - Lewicki, Sejnowksi - 1998
230	Exploratory projection pursuit - Friedman - 1987
216	Projection pursuit - Huber - 1985
214	A projection pursuit algorithm for exploratory data analysis - Friedman, JW - 1974
210	Unsupervised learning - Barlow - 1989
191	Single units and sensation: a neuron doctrine for perceptual psychology - Barlow - 1972
188	Independent component analysis using an extended infomax algorithm for mixed sub-gaussian and supergaussian sources - Lee, Girolami, et al. - 1999
188	Neural networks, principal components, and subspaces - Oja - 1989
185	Independent Component Analysis - Comon - 1991
173	Independent components analysis of electroencephalographic data - Jung, Makeig, et al. - 1996
143	Separation of a mixture of independent signals using time delayed correlations - Molgedey, Schuster - 1994
137	Non-linear neurons in the low noise limit: a factorial code maximises information transfer - Nadal, Parga - 1994
135	New criteria for blind deconvolution of non minimum phase systems (channels - Shalvi, Weinstein - 1990
121	Modern Factor Analysis, The - Harman - 1960
119	Adaptive blind separation of independent sources: a deflation approach - Delfosse, Loubaton - 1995
118	Separation of a mixture of independent sources through a maximum likelihood approach - Pham, Garrat, et al. - 1992
113	Independent component analysis—a new concept - Comon - 1994
111	A class of neural networks for independent component analysis. submitted to - Karhunen, Oja, et al. - 1996
105	A method of self-recovering equalization for multilevel amplitude-modulation - Sato - 1975
102	A dimension reduction framework for understanding cortical maps. Nature - Durbin, Mitchison - 1990
93	Independent component analysis of natural image sequences yields spatiotemporal filters similar to simple cells in primary visual cortex - Hateren, Ruderman - 1998
92	A context-sensitive generalization of ICA - Pearlmutter, Parra - 1996
90	A blind source separation technique based on second order statistics - Belouchrani, Meraim, et al. - 1997
90	On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix - Oja, Karhunen - 1985
87	Maximum likelihood for incomplete data via the EM algorithm - Dempster, Laird, et al. - 1977
87	Representation and separation of signals using nonlinear PCA type learning, Neural Networks 7 - Karhunen, Joutsensalo - 1994
86	Orientation selectivity, preference, and continuity in monkey striate cortex - Blasdel - 1992