Abstract
Many famous blind source separation (BSS) in frequency domain have been developed while they can still not avoid the permutation problem. We propose a new BSS approach for far-field broadband acoustic signals via combining the frequency invariant bemforming (FIB) technique and complex-valued independent component analysis (ICA). Compared with other frequency methods, our method can avoid the permutation problem and has much faster convergency rate. We also present a new performance measure to evaluate the separation. Finally, the simulation is given to verify the efficiency of the proposed method.
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Lv, Q., Zhang, X., Jia, Y. (2005). Blind Separation Combined Frequency Invariant Beamforming and ICA for Far-field Broadband Acoustic Signals. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_88
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DOI: https://doi.org/10.1007/11427445_88
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25913-8
Online ISBN: 978-3-540-32067-8
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