Abstract
We introduce a general criterion for blindly extracting a subset of sources in instantaneous mixtures. We derive the corresponding estimation equations and generalize them based on arbitrary nonlinear separating functions. A quasi-Newton algorithm for minimizing the criterion is presented, which reduces to the FastICA algorithm in the case when only one source is extracted. The asymptotic distribution of the estimator is obtained and a simulation example is provided.
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© 2006 Springer-Verlag Berlin Heidelberg
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Pham, DT.A. (2006). Blind Partial Separation of Instantaneous Mixtures of Sources. In: Rosca, J., Erdogmus, D., Príncipe, J.C., Haykin, S. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2006. Lecture Notes in Computer Science, vol 3889. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11679363_108
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DOI: https://doi.org/10.1007/11679363_108
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32630-4
Online ISBN: 978-3-540-32631-1
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