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Determination of the optimal Gabor wavelet shape for the best time-frequency localization using the entropy concept

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Abstract

The continuous Gabor wavelet transform (GWT) has been utilized as an effective and powerful time-frequency analysis tool for identifying the rapidly-varying characteristics of some dispersive wave signals. The effectiveness of the GWT is strongly influenced by the wavelet shape that controls the time-frequency localization property. Therefore, it is very important to choose the right Gabor wavelet shape for given signals. Because the characteristics of signals are rarely known in advance, the determination of the optimal shape is usually difficult. Based on this observation, we aim at developing a systematic method to determine the signal-dependent shape of the Gabor wavelet for the best time-frequency localization. To find the optimal Gabor wavelet shape, we employ the notion of the Shannon entropy that measures the extent of signal energy concentration in the time-frequency plane. To verify the validity of the present approach, we analyze a set of elastic bending wave signals generated by an impact in a solid cylinder.

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References

  1. Choi, H.I. andWilliams, W.J., “Improved Time-Frequency Representation of Multicomponent Signals Using Exponent Kernel,”IEEE Trans. Acoust. Speech Signal Process.,37 (6),862–871 (1989).

    Article  Google Scholar 

  2. Kim, Y.Y. andKim, E.-H., “Effectiveness of the Continuous Wavelet Transform in the Analysis of Some Dispersive Elastic Waves,”J. Acoust. Soc. Am.,110 (1),86–94 (2001).

    Article  Google Scholar 

  3. Kishimoto, K., Inoue, H., andShibuya, T., “Experimental Wavelet Analysis of Flexural Waves in Beams,” EXPERIMENTAL MECHANICS,36,212–217 (1996).

    Article  Google Scholar 

  4. Jeong, H. andJang, Y.S., “Fracture Source Location in a Thin Plate Using the Wavelet Transform of Dispersive Waves,”IEEE Trans. Ultra. Ferroelectr. Freq. Control,47,612–617 (2000).

    Article  Google Scholar 

  5. Jones, D.L. andParks, T.W., “A High Resolution Data-Adaptive Time-Frequency Representation,”IEEE Trans. Acoust. Speech Signal Process.,38 (12),2127–2135 (1990).

    Article  Google Scholar 

  6. Daubechies, I., Ten Lectures on Wavelets, SIAM, Philadelphia, PA (1992).

    Google Scholar 

  7. Mallat, S., A Wavelet Tour of Signal Processing, Academic Press, New York (1998).

    Google Scholar 

  8. Shannon, C., “A Mathematical Theory of Communication,”Bell Syst. Tech. J.,27,379–656 (1948).

    MathSciNet  Google Scholar 

  9. Coifman, R.R. andWickerhauser, M.V., “Entropy-Based Algorithms for the Best Basis Selection,”IEEE Trans. Inform. Theory,38 (2),713–718 (1992).

    Article  Google Scholar 

  10. Miklowitz, J., The Theory of Elastic Waves and Waveguides, North-Holland, New York (1978).

    Google Scholar 

  11. Doyle, J. F., Wave Propagation in Structures, Springer-Verlag, New York (1997).

    Google Scholar 

Download references

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Hong, J.C., Kim, Y.Y. Determination of the optimal Gabor wavelet shape for the best time-frequency localization using the entropy concept. Experimental Mechanics 44, 387–395 (2004). https://doi.org/10.1007/BF02428092

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  • DOI: https://doi.org/10.1007/BF02428092

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