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Supervised and Unsupervised Subband Adaptive Denoising Frameworks with Polynomial Threshold Function
Gong TR(宫铁瑞); Yang ZJ(杨志家); Wang GS(王庚善); Jiao P(焦平)
作者部门工业控制网络与系统研究室
发表期刊Mathematical Problems in Engineering
ISSN1024-123X
2017
卷号2017页码:1-12
收录类别SCI ; EI
EI收录号20171303490993
WOS记录号WOS:000398481000001
产权排序1
资助机构National Science and Technology Major Project of the Ministry of Science and Technology of China (no. Y6D8020801).
摘要Unlike inflexible structure of soft and hard threshold function, a unified linear matrix form with flexible structure for threshold function is proposed. Based on the unified linear flexible structure threshold function, both supervised and unsupervised subband adaptive denoising frameworks are established. To determine flexible coefficients, a direct mean-square error (MSE) minimization is conducted in supervised denoising while Stein's unbiased risk estimate as a MSE estimate is minimized in unsupervised denoising. The SURE rule requires no hypotheses or a priori knowledge about clean signals. Furthermore, we discuss conditions to obtain optimal coefficients for both supervised and unsupervised subband adaptive denoising frameworks. Applying an Odd-Term Reserving Polynomial (OTRP) function as concrete threshold function, simulations for polynomial order, denoising performance, and noise effect are conducted. Proper polynomial order and noise effect are analyzed. Both proposed methods are compared with soft and hard based denoising technologies - VisuShrink, SureShrink, MiniMaxShrink, and BayesShrink - in denoising performance simulation. Results show that the proposed approaches perform better in both MSE and signal-to-noise ratio (SNR) sense.
语种英语
WOS标题词Science & Technology ; Technology ; Physical Sciences
WOS类目Engineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications
关键词[WOS]WAVELET SHRINKAGE ; NOISE ESTIMATION ; DOMAIN ; DISTRIBUTIONS
WOS研究方向Engineering ; Mathematics
引用统计
被引频次:1[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/20295
专题工业控制网络与系统研究室
通讯作者Gong TR(宫铁瑞)
作者单位1.Department of Industrial Control Networks and Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
推荐引用方式
GB/T 7714
Gong TR,Yang ZJ,Wang GS,et al. Supervised and Unsupervised Subband Adaptive Denoising Frameworks with Polynomial Threshold Function[J]. Mathematical Problems in Engineering,2017,2017:1-12.
APA Gong TR,Yang ZJ,Wang GS,&Jiao P.(2017).Supervised and Unsupervised Subband Adaptive Denoising Frameworks with Polynomial Threshold Function.Mathematical Problems in Engineering,2017,1-12.
MLA Gong TR,et al."Supervised and Unsupervised Subband Adaptive Denoising Frameworks with Polynomial Threshold Function".Mathematical Problems in Engineering 2017(2017):1-12.
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