Performance Analysis of a Robust Wavelet Threshold for Heavy-Tailed Noises

Abstract:

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The interesting signal is often contaminated by heavy-tailed noise that has more outliers than Gaussian noise. A robust wavelet threshold based on the minimax description length principle is derived in the ε-contaminated normal family for maximizing the entropy. Compared with classical threshold based on Gaussian assumption, the robust threshold can eliminate the heavy-tailed noise better, even if the precise value of ε is unknown, which shows its robustness. The further experiment shows that soft threshold is more suitable than hard threshold for robust wavelet threshold technique.

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Periodical:

Edited by:

Zhu Zhilin & Patrick Wang

Pages:

979-984

DOI:

10.4028/www.scientific.net/AMM.40-41.979

Citation:

G. F. Wei et al., "Performance Analysis of a Robust Wavelet Threshold for Heavy-Tailed Noises", Applied Mechanics and Materials, Vols. 40-41, pp. 979-984, 2011

Online since:

November 2010

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$35.00

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