Zeller M, Azpicueta-Ruiz LA, Kellermann W (2009)
Publication Language: English
Publication Status: Published
Publication Type: Conference contribution, Conference Contribution
Publication year: 2009
Pages Range: 2965-2968
Article Number: 4960246
ISBN: 978-1-4244-2353-8
DOI: 10.1109/ICASSP.2009.4960246
This paper presents a method for estimating the optimum memory size for identification of an unknown second-order Volterra kernel. As these structures may imply considerable computational demands, it is highly desirable to design adaptive realizations with a minimum number of coefficients. Therefore, we propose a combination scheme comprising two Volterra filters with time-variant sizes of the actually used quadratic kernels. By following some simple rules, the number of diagonals in the quadratic kernels is increased or decreased in order to find the optimum memory configuration in parallel to the coefficient adaptation. Thus, the arbitrary choice of the nonlinear system size is overcome by a dynamically growing/ shrinking system. Experimental results for various signals and nonlinear scenarios demonstrate the effectiveness of the proposed method. ©2009 IEEE.
APA:
Zeller, M., Azpicueta-Ruiz, L.A., & Kellermann, W. (2009). Online estimation of the optimum quadratic kernel size of second-order Volterra filters using a convex combination scheme. In Proceedings of the 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 (pp. 2965-2968). Taipei, TW.
MLA:
Zeller, Marcus, Luis A. Azpicueta-Ruiz, and Walter Kellermann. "Online estimation of the optimum quadratic kernel size of second-order Volterra filters using a convex combination scheme." Proceedings of the 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009, Taipei 2009. 2965-2968.
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