Blind separation of convolutive mixtures: a Gauss-Newton algorithm
- 22 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 326-330
- https://doi.org/10.1109/host.1997.613540
Abstract
This paper addresses the blind separation of convolutive mixtures of independent and non-Gaussian sources. We present a block-based Gauss-Newton algorithm which is able to obtain a separation solution using only a specific set of output cross-cumulants and the hypothesis of soft mixtures. The order of the cross-cumulants is chosen to obtain a particular form of the Jacobian matrix that ensures convergence and reduces computational burden. The method can be seen as an extension and improvement of the Van-Gerven's symmetric adaptive decorrelation (SAD) method. Moreover the convergence analysis presented in the paper provides a theoretical background to derive an improved version of the Nguyen-Jutten (1995) algorithm.Keywords
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