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Hierarchical-likelihood-based wavelet method for denoising signals with missing data
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DOI：10.1109/LSP.2006.871713.png)
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摘要
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This letter proposes a wavelet denoising method in the presence of missing data. This approach is based on a coupling of wavelet shrinkage and hierarchical (or h)-likelihood method. The h-likelihood provides an effective imputation methodology of missing data to give wavelet estimators for signals and motivates a fast and simple algorithm. The method can be easily extended to other settings, such as image denoising. Simulation studies demonstrate empirical properties of the proposed method.
Keyword:
h-likelihood
imputation
missing
wavelet denoising
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期刊
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9.6
论文数:
1.1W
被引数:
1.7W
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