Journal ArticleDOI
Indeterminacy and identifiability of blind identification
TLDR
In this article, a mathematical structure from which the acceptable indeterminacy is represented by an equivalence relation is formulated, and two identifiable cases are shown along with blind identification algorithms, FOBI (fourth-order blind identification), EFOBI (extended FOBI), and AMUSE algorithm.Abstract:
Blind identification of source signals is studied from both theoretical and algorithmic aspects. A mathematical structure is formulated from which the acceptable indeterminacy is represented by an equivalence relation. The concept of identifiability is then defined. Two identifiable cases are shown along with blind identification algorithms. The performance of FOBI (fourth-order blind identification), EFOBI (extended FOBI), and AMUSE algorithms is evaluated by some heuristic arguments and simulation results. It is shown that EFOBI outperforms the FOBI algorithm, and the AMUSE algorithm performs better than EFOBI in the case of nonwhite source signals. AMUSE is applied to a speech extraction problem and shown to have promising results. >read more
Citations
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Journal ArticleDOI
Blind beamforming for non-gaussian signals
TL;DR: In this paper, a computationally efficient technique for blind estimation of directional vectors, based on joint diagonalization of fourth-order cumulant matrices, is presented for beamforming.
Journal ArticleDOI
A blind source separation technique using second-order statistics
TL;DR: A new source separation technique exploiting the time coherence of the source signals is introduced, which relies only on stationary second-order statistics that are based on a joint diagonalization of a set of covariance matrices.
Journal ArticleDOI
Equivariant adaptive source separation
TL;DR: A class of adaptive algorithms for source separation that implements an adaptive version of equivariant estimation and is henceforth called EASI, which yields algorithms with a simple structure for both real and complex mixtures.
Journal ArticleDOI
Convolutive blind separation of non-stationary sources
Lucas C. Parra,Clay D. Spence +1 more
TL;DR: This work tackles the problem of source separation by explicitly exploiting the nonstationarity of the acoustic sources, and finds an FIR backward model, which generates well separated model sources.
Journal ArticleDOI
Adaptive blind signal processing-neural network approaches
Shun-ichi Amari,Andrzej Cichocki +1 more
TL;DR: Learning algorithms and underlying basic mathematical ideas are presented for the problem of adaptive blind signal processing, especially instantaneous blind separation and multichannel blind deconvolution/equalization of independent source signals.
References
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