Abstract
The principal aim of this work is to demonstrate, from an empirical point of view, the effectiveness of a previously proposed technique for the Blind Source Separation (BSS) with Post Non Linear (PNL) underdetermined instantaneous mixing model (uBSS), in the more complex and realistic case where delayed sources are considered in the linear part of the mixing (PNL-uBSS with delays). The proposed approach is composed of two consecutive stages: in the first stage the inverse nonlinearities are estimated by Gaussianization of the mixtures; in the second stage source signals are extracted from the linearized mixtures using a three step approach already known in the literature for linear delayed uBSS. An improved technique based on Extended Gaussianization is also provided for the estimation of inverse nonlinearities. Experimental results using synthetic mixtures of real world data (speech signals) are given to prove the effectiveness of the proposed approach.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Cichocky, A., Amari, S.: Adaptive Blind Signal and Image Processing: Learing Algorithms and Applicatins. John Wiley and Sons, Chichester (2001)
Hyvrinen, A., Karhunen, J., Oja, E.: Independent Component Analysis. Wiley & Sons, New York (2001)
Taleb, A., Jutten, C.: Source Separation in Post-Nonlinear Mixtures. IEEE Trans. on Signal Processing 47(10), 2807–2820 (1999)
Squartini, S., Bastari, A., Piazza, F.: A Practical Approach Based on Gaussianization for Post-Nonlinear Underdetermined BSS. In: Proc. ICCCAS, Guilin, China (2006)
Bofill, P.: Underdetermined Blind Separation of Delayed Sound Sources in the Frequency Domain. Neurocomputing, Special Issue ICA and BSS (2001)
Zhang, K., Chan, L.W.: Extended Gaussianization Method for Blind Separation of Post-Nonlinear Mixtures. Neural Computation 17, 425–452 (2005)
Chen, S.S., Gonipath, R.A.: Gaussianization. In: Proc. NIPS, Denver, USA (2000)
Ziehe, A., Kawanabe, M., Harmeling, S., Mueller, K.R.: Blind Separation of Post-Nonlinear Mixtures Using Gaussianizing Transformations and Temporal Decorrelation. In: Proc. ICA2003, pp. 269–274 (2003)
Papoulis, A., Pillai, S.U.: Probability, Random Variables and Stochastic Process, 4th edn. McGraw-Hill, New York (2002)
Bastari, A., Squartini, S., Piazza, F.: Underdetermined Blind Separation of Speech Signals with Delays in Different Time-Frequency Domains. In: Chollet, G., Esposito, A., Faúndez-Zanuy, M., Marinaro, M. (eds.) Nonlinear Speech Modeling and Applications. LNCS (LNAI), vol. 3445, pp. 136–163. Springer, Heidelberg (2005)
Lobo, M.S., Vandenberghe, L., Boyd, S., Lebret, H.: Applications of Second-order Cone Programming. Linear Algebra and Its Applications (1998)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Bastari, A., Squartini, S., Cecchi, S., Piazza, F. (2007). Gaussianization Based Approach for Post-Nonlinear Underdetermined BSS with Delays. In: Liu, D., Fei, S., Hou, Z., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4493. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72395-0_96
Download citation
DOI: https://doi.org/10.1007/978-3-540-72395-0_96
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72394-3
Online ISBN: 978-3-540-72395-0
eBook Packages: Computer ScienceComputer Science (R0)