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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
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ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  3/2011 - 9

 HIGH-IMPACT PAPER 

Alleviating Border Effects in Wavelet Transforms for Nonlinear Time-varying Signal Analysis

SU, H. See more information about SU, H. on SCOPUS See more information about SU, H. on IEEExplore See more information about SU, H. on Web of Science, LIU, Q. See more information about  LIU, Q. on SCOPUS See more information about  LIU, Q. on SCOPUS See more information about LIU, Q. on Web of Science, LI, J. See more information about LI, J. on SCOPUS See more information about LI, J. on SCOPUS See more information about LI, J. on Web of Science
 
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Download PDF pdficon (1,649 KB) | Citation | Downloads: 1,172 | Views: 5,002

Author keywords
convolution, Fourier series, frequency estimation, spectrogram, wavelet transforms

References keywords
wavelet(14), signal(13), processing(10), transform(7), filter(6), signals(5), banks(5), wavelets(4), time(4), symmetric(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2011-08-31
Volume 11, Issue 3, Year 2011, On page(s): 55 - 60
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.03009
Web of Science Accession Number: 000296186700009
SCOPUS ID: 80055067358

Abstract
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Border effects are very common in many finite signals analysis and processing approaches using convolution operation. Alleviating the border effects that can occur in the processing of finite-length signals using wavelet transform is considered in this paper. Traditional methods for alleviating the border effects are suitable to compression or coding applications. We propose an algorithm based on Fourier series which is proved to be appropriate to the application of time-frequency analysis of nonlinear signals. Fourier series extension method preserves the time-varying characteristics of the signals. A modified signal duration expression for measuring the extent of border effects region is presented. The proposed algorithm is confirmed to be efficient to alleviate the border effects in comparison to the current methods through the numerical examples.


References | Cited By  «-- Click to see who has cited this paper

[1] B. C. B. Chan, F. H. Y. Chan, F. K. Lam, P. W. Lui and P. W. F. Poon, "Fast detection of venous air embolism is Doppler heart sound using the wavelet transform," IEEE Trans. Biomed. Eng., vol. 44, pp. 237-245, Apr. 1997.
[CrossRef] [Web of Science Times Cited 35] [SCOPUS Times Cited 41]


[2] N. Ghaffarzadeh and B. Vahidi, "A New protection scheme for high impedance fault detection using wavelet packet transform," Advances in Electrical and Computer Engineering, vol. 10, pp. 17-20, Mar. 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 9] [SCOPUS Times Cited 15]


[3] A. Jardine, D. Lin and D. Banjevic, "A review on machinery diagnostics and prognostics implementing condition-based maintenance," Mech. Syst. Signal Process, vol. 20, pp. 1483-1510, Oct. 2006.
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[CrossRef] [Web of Science Times Cited 53] [SCOPUS Times Cited 67]


[6] P. S. Addison, The Illustrated Wavelet Transform Handbook: Introductory Theory and Applications in Science, Engineering, Medicine and Finance. Bristol, U.K.: IOP Publishing Ltd, 2002.

[7] A. Cohen, I. Daubechies, and P. Vial, "Wavelets on the interval and fast wavelet transforms," Applied Comput. Harmon. Anal., vol. 1, pp. 54-81, Jan. 1993.
[CrossRef] [SCOPUS Times Cited 744]


[8] C. M. Brislawn, "Classification of nonexpansive symmetric extension transform for multirate filter banks," Appl. Comput. Harmon. Anal., vol. 3, pp. 337-357, Oct. 1996.
[CrossRef] [Web of Science Times Cited 64] [SCOPUS Times Cited 82]


[9] V. Silva and L. de Sá, "General method for perfect reconstruction subband processing of finite length signals using linear extensions," IEEE Trans. Signal Processing, vol. 47, pp. 2572-2575, Sep. 1999.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 13]


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[CrossRef] [Web of Science Times Cited 68] [SCOPUS Times Cited 95]


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[CrossRef] [SCOPUS Times Cited 31]


[12] M. Ferretti and D. Rizzo, "Handling Borders in Systolic Architectures for the 1-D Discrete Wavelet Transform for Perfect Reconstruction," IEEE Trans. Signal Processing, vol. 48, pp. 1365-1378, May 2000.
[CrossRef] [Web of Science Times Cited 18] [SCOPUS Times Cited 28]


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[CrossRef] [Web of Science Times Cited 37] [SCOPUS Times Cited 49]


[14] M. D. Jiménez and N. Prelcic, "Linear boundary extensions for finite length signals and paraunitary two-channel filterbanks," IEEE Trans. Signal Process, vol. 52, pp. 3213-3226, Nov. 2004.
[CrossRef] [Web of Science Times Cited 11] [SCOPUS Times Cited 14]


[15] G. Strang and T. Q. Nguyen, Wavelets and Filterbanks. Wellesley, MA: Wellesley-Cambridge, 1996.

[16] S. Mallat, A Wavelet Tour of Signal Processing, 3rd ed. New York: Academic, 2008.

[17] J. Liang and T. Parks, "Image coding using translation invariant wavelet transforms with symmetric extensions," IEEE Trans. Image Processing, vol. 7, pp. 762-769, May 1998.
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 11]


[18] J. Lin and M. J. T. Smith, "New perspectives and improvements on the symmetric extension filter bank for subband /wavelet image compression," IEEE Trans. Image Processing, vol. 17, pp. 177-180, Feb. 2008.
[CrossRef] [Web of Science Times Cited 16] [SCOPUS Times Cited 23]


[19] U. Sezen, "Perfect reconstruction IIR digital filter banks supporting nonexpansive linear signal extensions," IEEE Trans. Signal Processing, vol. 57, pp. 2140-2150, Jun. 2009.
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 4]


[20] A. Mertins, Signal Analysis: Wavelet, Filter Banks, Time-Frequency Transforms and Applications. Chichester, U.K.: Wiley, 1999.

[21] J. N. Bradley, C. M. Brislawn, and V. Faber, "Reflected boundary conditions for multirate filter banks," in Proc. IEEE Int. Symp. Time-Frequency and Time-Scale Analysis, Victoria, BC, Canada, Oct. 1992, pp. 307-310.
[CrossRef] [SCOPUS Times Cited 15]


[22] S. J. Huang and C. T. Hsieh, "Application of Morlet wavelets to supervise power system disturbances," IEEE Trans. Power Delivery, vol. 14, pp. 235-243, Jan. 1999.
[CrossRef] [Web of Science Times Cited 105] [SCOPUS Times Cited 192]


[23] S. S. Osofsky, "Calculation of transient sinusoidal signal amplitudes using the Morlet wavelet," IEEE Trans. Signal Processing, vol. 47, pp. 3426-3428, Dec. 1999.
[CrossRef] [Web of Science Times Cited 10] [SCOPUS Times Cited 13]


[24] R. A. Carmona, W. L. Hwang, and B. Torresani, "Characterization of signals by the ridge of their wavelet ridge," IEEE Trans. Signal Processing, vol. 45, pp. 2586-2590, Oct. 1997.
[CrossRef] [Web of Science Times Cited 239] [SCOPUS Times Cited 288]


[25] D. Gabor, "Theory of communication," J. IEE, vol. 93, pp. 429-457, Nov. 1946.
[CrossRef]


References Weight

Web of Science® Citations for all references: 3,170 TCR
SCOPUS® Citations for all references: 4,966 TCR

Web of Science® Average Citations per reference: 127 ACR
SCOPUS® Average Citations per reference: 199 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2022-08-05 20:18 in 124 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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