Dependent Component Analysis
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Citation: EURASIP Journal on Advances in Signal Processing 2013 2013:185
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Independent vector analysis using subband and subspace nonlinearity
Independent vector analysis (IVA) is a recently proposed technique, an application of which is to solve the frequency domain blind source separation problem. Compared with the traditional complex-valued indepe...
Citation: EURASIP Journal on Advances in Signal Processing 2013 2013:74 -
Separation of instantaneous mixtures of a particular set of dependent sources using classical ICA methods
This article deals with the problem of blind source separation in the case of a linear and instantaneous mixture. We first investigate the behavior of known independent component analysis (ICA) methods in the ...
Citation: EURASIP Journal on Advances in Signal Processing 2013 2013:62 -
Restoration of recto–verso colour documents using correlated component analysis
In this article, we consider the problem of removing see-through interferences from pairs of recto–verso documents acquired either in grayscale or RGB modality. The see-through effect is a typical degradation ...
Citation: EURASIP Journal on Advances in Signal Processing 2013 2013:58 -
Separation of phase-locked sources in pseudo-real MEG data
This article addresses the blind separation of linear mixtures of synchronous signals (i.e., signals with locked phases), which is a relevant problem, e.g., in the analysis of electrophysiological signals of t...
Citation: EURASIP Journal on Advances in Signal Processing 2013 2013:32 -
On the conditions for valid objective functions in blind separation of independent and dependent sources
It is well known that independent sources can be blindly detected and separated, one by one, from linear mixtures by identifying local extrema of certain objective functions (contrasts), like negentropy, non-Gaus...
Citation: EURASIP Journal on Advances in Signal Processing 2012 2012:255 -
Non-unitary matrix joint diagonalization for complex independent vector analysis
Independent vector analysis (IVA) is a special form of independent component analysis (ICA), which has demonstrated its prominent performance in solving convolutive blind source separation (BSS) problems in th...
Citation: EURASIP Journal on Advances in Signal Processing 2012 2012:241 -
Dependent Gaussian mixture models for source separation
Source separation is a common task in signal processing and is often analogous to factor analysis. In this study, we look at a factor analysis model for source separation of multi-spectral image data where pri...
Citation: EURASIP Journal on Advances in Signal Processing 2012 2012:239 -
Audio video based fast fixed-point independent vector analysis for multisource separation in a room environment
Fast fixed-point independent vector analysis (FastIVA) is an improved independent vector analysis (IVA) method, which can achieve faster and better separation performance than original IVA. As an example IVA m...
Citation: EURASIP Journal on Advances in Signal Processing 2012 2012:183