Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32131
Improved Approximation to the Derivative of a Digital Signal Using Wavelet Transforms for Crosstalk Analysis

Authors: S. P. Kozaitis, R. L. Kriner


The information revealed by derivatives can help to better characterize digital near-end crosstalk signatures with the ultimate goal of identifying the specific aggressor signal. Unfortunately, derivatives tend to be very sensitive to even low levels of noise. In this work we approximated the derivatives of both quiet and noisy digital signals using a wavelet-based technique. The results are presented for Gaussian digital edges, IBIS Model digital edges, and digital edges in oscilloscope data captured from an actual printed circuit board. Tradeoffs between accuracy and noise immunity are presented. The results show that the wavelet technique can produce first derivative approximations that are accurate to within 5% or better, even under noisy conditions. The wavelet technique can be used to calculate the derivative of a digital signal edge when conventional methods fail.

Keywords: digital signals, electronics, IBIS model, printedcircuit board, wavelets

Digital Object Identifier (DOI):

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1726


[1] J. Song, K. Hoover and E. Wheeler, "Effectiveness of PCB Simulation in Teaching High-Speed Digital Design," in Conf. Rec. 2007 IEEE International Symposium on Electromagnetic Compatibility, pp. 1-6.
[2] M. Basu, "Gaussian-based edge-detection methods - A survey," IEEE Trans. on Systems, Man and Cybernetics Part C: Applications and Reviews, vol. 32, no. 3, pp. 252-260, 2002.
[3] F. Faghih, and M. Smith, "Combining spatial and scale-space techniques for edge detection to provide a spatially adaptive wavelet-based noise filtering algorithm," IEEE Trans. on Image Processing, vol. 11, no. 9, pp, 1062-1071, 2002.
[4] A. Leung , F.-T. Chau, and J.-B. Gao, "Wavelet Transform: A Method for Derivative Calculation in Analytical Chemistry," Analytical Chemistry, vol. 70, no. 24, pp. 5222-5229, Dec. 1998.
[5] Y. Lee, and S. P. Kozaitis, "Multiresolution gradient-based edge detection in noisy images using wavelet domain filters," Optical Engineering, vol. 39, no. 9, pp, 2405-2412, 2000.
[6] A. Kacha, F. Grenez, P. De Doncker, and K. Benmahammed, "A wavelet-based approach for disturbance line identification in printed circuit boards," J. of Electromagn. Waves and Appl., vol. 18, no. 5, pp. 675-690, 2004.
[7] G. Antonini and A. Orlandi, "Wavelet packet-based EMI signal processing and source identification," IEEE Trans. Electromagn. Compat., vol. 43, no. 2, pp. 140-148, May 2001.