Paper Title:
Performance Analysis of a Robust Wavelet Threshold for Heavy-Tailed Noises
  Abstract

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.

  Info
Periodical
Edited by
Zhu Zhilin & Patrick Wang
Pages
979-984
DOI
10.4028/www.scientific.net/AMM.40-41.979
Citation
G. F. Wei, F. Su, T. Jian, "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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