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MIMO Instantaneous Blind Identification Based on Second-Order Temporal Structure and Newton’s Method

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5855))

Abstract

This paper presents a new MIMO instantaneous blind identification algorithm based on second order temporal property and Newton’s Method. Second order temporal structure is reformulated in a particular way such that each column of the unknown mixing matrix satisfies a system of nonlinear multivariate homogeneous polynomial equations. The nonlinear system is solved by Newton’s method for the equations. Our algorithm allows estimating the mixing matrix for scenarios with 4 sources and 3 sensors, etc. Simulations and comparisons show its effective with more accurate solutions than the algorithm with homotopy method.

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References

  1. Cichocki, A., Amari, S.I.: Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications. Wiley, New York (2002)

    Book  Google Scholar 

  2. van de Laar, J., Moonen, M., Sommen, P.C.W.: MIMO Instantaneous Blind Identification Based on Second-Order Temporal Structure. IEEE Transactions on Signal Processing 56(9), 4354–4364 (2008)

    Article  Google Scholar 

  3. Shen, X., Shi, X.: On-line Blind Equalization Algorithm of an FIR MIMO channel system for Non-Stationary Signals. IEE Proceedings Vision, Image & Signal Processing 152(5), 575–581 (2005)

    Article  Google Scholar 

  4. Shen, X., Haixiang, X., Cong, F., et al.: Blind Equalization Algorithm of FIR MIMO System in Frequency Domain. IEE Proceedings Vision, Image & Signal Processing 153(5), 703–710 (2006)

    Article  Google Scholar 

  5. Hua, Y., Tugnait, J.K.: Blind identifiability of FIR-MIMO systems with colored input using second order statistics. IEEE Signal Processing Letters 7(12), 348–350 (2000)

    Article  Google Scholar 

  6. Lindgren, U., van der Veen, A.-J.: Source separation based on second order statistics—An algebraic approach. In: Proc. IEEE SP Workshop Statistical Signal Array Processing, Corfu, Greece, June 1996, pp. 324–327 (1996)

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  7. Burden, R.L., Faires, J.D.: Numerical Analysis, pp. 600–635. Thomson Learning, Inc. (2001)

    Google Scholar 

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© 2009 Springer-Verlag Berlin Heidelberg

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Shen, X., Meng, G. (2009). MIMO Instantaneous Blind Identification Based on Second-Order Temporal Structure and Newton’s Method. In: Deng, H., Wang, L., Wang, F.L., Lei, J. (eds) Artificial Intelligence and Computational Intelligence. AICI 2009. Lecture Notes in Computer Science(), vol 5855. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05253-8_55

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  • DOI: https://doi.org/10.1007/978-3-642-05253-8_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05252-1

  • Online ISBN: 978-3-642-05253-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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