Blind deconvolution of ultrasonic signals using high-order spectral analysis and wavelets

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Abstract

Defect detection by ultrasonic method is limited by the pulse width. Resolution can be improved through a deconvolution process with a priori information of the pulse or by its estimation. In this paper a regularization of the Wiener filter using wavelet shrinkage is presented for the estimation of the reflectivity function. The final result shows an improved signal to noise ratio with better axial resolution. © Springer-Verlag Berlin Heidelberg 2005.

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APA

Herrera, R. H., Moreno, E., Calas, H., & Orozco, R. (2005). Blind deconvolution of ultrasonic signals using high-order spectral analysis and wavelets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3773 LNCS, pp. 663–670). https://doi.org/10.1007/11578079_69

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