Abstract
Sinusoidal interferences are found in ultrasonic signals when we try to characterize a material, as for example interferences coming from PC cards. We are interested in obtaining a robust method that cancels these interferences preserving the waveform of the signal. A Blind Source Separation method to extract these sinusoids is presented in this paper. We will get so many linear mixtures of the backscattering echo of the material and the sinusoids as we need from different pulse responses of the material.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
P. Comon, “Independent Component Analysis, a New Concept?,” Signal Processing, vol. 36, no. 3, 1994, pp. 287-314.
V.M. Narayanan, P.M. Shankar, L. Vergara, and J.M. Reid, “Studies on Ultrasonic Scattering from Quasi-Periodic Structures,” IEEE Trans. on Ultrasonics, Ferroelectrics and Frequency Control, vol. 44, no. 1, Jan. 1997.
J.F. Cardoso, “Blind Signal Separation: Statistical Principles,” Proc. of the IEEE, vol. 86, no. 10, 1998, pp. 2009-2025.
S. Amari and A. Cichocki, “Adaptive Blind Signal Processing, Neural Network Approaches,” Proceedings of the IEEE, vol. 86, no. 10, 1998, pp. 2026-2048.
A. Hyvarinen and E. Oja, “Independent Component Analysis: Algorithms and Applications,” Neural Networks, vol. 13, 2000, pp. 411-430.
T.-W. Lee, Independent Component Analysis, Kluwer Academic Publishers, 1998.
Advances in Independent Component Analysis, Mark. Girolami (Ed.), Springer, 2000.
Independent Component Analysis, Principles and Practice, S. Roberts and R. Everson (Eds.), Cambridge University Press, 2001.
E. Oja, A. Hyvarinen, and J. Karhunen, Independent Component Analysis, John Wiley & Sons, 2001.
A. Stuart and J.K. Ord, Kendall's Advanced Theory of Statistics, vol. 1, 6th edition, London: Edward Arnold, 1994.
A. Papoulis, Probability, Random Variables, and Stochastic Processes, 3rd. edition, McGraw-Hill, 1991.
S. Kay, Spectral Estimation: Theory and Application, Prentice-Hall, 1988.
L. Vergara, “New Insights into the High-Order Yule-Walker Equations,” IEEE Trans. on Acoust. Speech and Signal Processing, vol. 38, no. 9, 1990, pp. 1650-1651.
P.A. Regalia, Adaptive IIR Filtering in Signal Processing and Control, Marcel Dekker, 1994.
A. Nehorai, “A Minimal Parameter Adaptive Notch Filter with Constrained Poles and Zeros,” IEEE Trans. on Acoust. Speech and Signal Processing, vol. 33, no. 4, 1985, pp. 983-996.
P.A. Regalia, “An Improved Lattice Based Adaptive IIR Notch Filter,” IEEE Trans. on Signal Processing, vol. 39, no. 9, 1991, pp. 2124-2128.
G. Piñero and L. Vergara, “Applying Acoustic Array Processing to the Estimation of the Propagation Speed of Waves in a Car Exhaust,” in Proc. of 1997 International Conference on Acoustics, Speech and Signal Processing, ICASSP-97, 1997, pp. 3841-3844, Munich (Germany).
L. Vergara and J.M. Páez, “Backscattering Grain Noise Modelling in Ultrasonic Non-Destructive Testing,” Waves in Random Media, vol. 1, 1991, pp. 81-92.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Igual, J., Camacho, A. & Vergara, L. A Blind Source Separation Technique for Extracting Sinusoidal Interferences in Ultrasonic Non-Destructive Testing. The Journal of VLSI Signal Processing-Systems for Signal, Image, and Video Technology 38, 25–34 (2004). https://doi.org/10.1023/B:VLSI.0000028531.67904.9e
Published:
Issue Date:
DOI: https://doi.org/10.1023/B:VLSI.0000028531.67904.9e