Abstract
In this paper we propose and investigate a recursive approach for blind source separations (BSS) or/and for independent component analyses (ICA). Based on this approach we present a deterministic (without a stochastic learning) algorithm for real-time blind source separation of convolutive mixing. When employed to acoustic signals, the algorithm shows a superior rate of convergence over its counterpart of gradient-based approach based on our simulations. By applying the algorithm in a real-time BSS system for realistic acoustic signals, we also give experiments to illustrate the effectiveness and validity of the algorithm.
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© 2003 Springer-Verlag Berlin Heidelberg
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Ding, S., Huang, J. (2003). Recursive Approach for Real-Time Blind Source Separation of Acoustic Signals. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45224-9_196
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DOI: https://doi.org/10.1007/978-3-540-45224-9_196
Publisher Name: Springer, Berlin, Heidelberg
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