Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 1999.07g
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- Pages.2956-2958
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- 1999
Wavelet Denoising based on a Bayesian Approach
Bayesian 방법에 의한 잡음감소 방법에 관한 연구
- Lee, Moon-Jik (Dept. of Control & Instrumentation Engineering, Kwangwoon Univ.) ;
- Chung, Chin-Hyun (Dept. of Control & Instrumentation Engineering, Kwangwoon Univ.)
- Published : 1999.07.19
Abstract
The classical solution to the noise removal problem is the Wiener filter, which utilizes the second-order statistics of the Fourier decomposition. We discuss a Bayesian formalism which gives rise to a type of wavelet threshold estimation in non-parametric regression. A prior distribution is imposed on the wavelet coefficients of the unknown response function, designed to capture the sparseness of wavelet expansion common to most application. For the prior specified, the posterior median yields a thresholding procedure
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