Hierarchical-likelihood-based wavelet method for denoising signals with missing data
- Authors
- Kim, Donghoh; Lee, Youngjo; Oh, Hee-Seok
- Issue Date
- Jun-2006
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- h-likelihood; imputation; missing; wavelet denoising
- Citation
- IEEE SIGNAL PROCESSING LETTERS, v.13, no.6, pp.361 - 364
- Journal Title
- IEEE SIGNAL PROCESSING LETTERS
- Volume
- 13
- Number
- 6
- Start Page
- 361
- End Page
- 364
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/24553
- DOI
- 10.1109/LSP.2006.871713
- ISSN
- 1070-9908
- Abstract
- 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.
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Collections - College of Business Management > 국제경영학과 > 1. Journal Articles
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