Book ChapterDOI
TDSEP — an efficient algorithm for blind separation using time structure
Andreas Ziehe,Klaus-Robert Müller +1 more
- pp 675-680
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An algorithm for blind source separation based on several time-delayed second order correlation matrices is proposed and its efficiency and stability are demonstrated for linear artificial mixtures with 17 sources.Abstract:
An algorithm for blind source separation based on several time-delayed second order correlation matrices is proposed. The technique to construct the unmixing matrix employs first a whitening step and then an approximate simultaneous diagonalisation of several time-delayed second order correlation matrices. Its efficiency and stability are demonstrated for linear artificial mixtures with 17 sources.read more
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Journal ArticleDOI
Estimating mutual information.
TL;DR: Two classes of improved estimators for mutual information M(X,Y), from samples of random points distributed according to some joint probability density mu(x,y), based on entropy estimates from k -nearest neighbor distances are presented.
Reference EntryDOI
Independent Component Analysis
Hannu Oja,Klaus Nordhausen +1 more
TL;DR: A statistical generative model called independent component analysis is discussed, which shows how sparse coding can be interpreted as providing a Bayesian prior, and answers some questions which were not properly answered in the sparse coding framework.
Book
Handbook of Blind Source Separation: Independent Component Analysis and Applications
Pierre Comon,Christian Jutten +1 more
TL;DR: This handbook provides the definitive reference on Blind Source Separation, giving a broad and comprehensive description of all the core principles and methods, numerical algorithms and major applications in the fields of telecommunications, biomedical engineering and audio, acoustic and speech processing.
Journal ArticleDOI
Independent component approach to the analysis of EEG and MEG recordings
TL;DR: ICA has been shown to be an efficient tool for artifact identification and extraction from electroencephalographic and magnetoencephalographical recordings and has been applied to the analysis of brain signals evoked by sensory stimuli.
Journal ArticleDOI
EEG artifact removal?state-of-the-art and guidelines
TL;DR: This paper presents an extensive review on the artifact removal algorithms used to remove the main sources of interference encountered in the electroencephalogram (EEG), specifically ocular, muscular and cardiac artifacts, and concludes that the safest approach is to correct the measured EEG using independent component analysis-to be precise, an algorithm based on second-order statistics such as second- order blind identification (SOBI).
References
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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
A fast fixed-point algorithm for independent component analysis
Aapo Hyvärinen,Erkki Oja +1 more
TL;DR: A novel fast algorithm for independent component analysis is introduced, which can be used for blind source separation and feature extraction, and the convergence speed is shown to be cubic.
Journal ArticleDOI
Blind separation of auditory event-related brain responses into independent components
TL;DR: This paper reports the application of a method based on information theory that decomposes one or more ERPs recorded at multiple scalp sensors into a sum of components with fixed scalp distributions and sparsely activated, maximally independent time courses.
Journal ArticleDOI
Jacobi Angles for Simultaneous Diagonalization
TL;DR: This note gives the required Jacobi angles in close form for simultaneous diagonalization of several matrices.