An Improved Wavelet Threshold De-Noising Data Processing Method Research in Deformation Monitoring

Abstract:

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Due to the soft and hard threshold function exist shortcomings. This will reduce the performance in wavelet de-noising. in order to solve this problem,This article proposes Modulus square approach. the new approach avoids the discontinuity of the hard threshold function and also decreases the fixed bias between the estimated wavelet coefficients and the wavelet coefficients of the soft-threshold method.Simulation results show that SNR and MSE are better than simply using soft and hard threshold,having good de-noising effect in Deformation Monitoring.

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Periodical:

Edited by:

Xuejun Zhou

Pages:

2858-2863

DOI:

10.4028/www.scientific.net/AMM.90-93.2858

Citation:

W. Li and X. Wang, "An Improved Wavelet Threshold De-Noising Data Processing Method Research in Deformation Monitoring", Applied Mechanics and Materials, Vols. 90-93, pp. 2858-2863, 2011

Online since:

September 2011

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Price:

$35.00

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