Supervised and Unsupervised Subband Adaptive Denoising Frameworks with Polynomial Threshold Function

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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)
刊名	Mathematical Problems in Engineering
	2017
卷号	2017 页码:1-12
ISSN号	1024-123X
通讯作者	宫铁瑞
产权排序	1
中文摘要	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.
WOS标题词	Science & Technology ; Technology ; Physical Sciences
类目[WOS]	Engineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications
研究领域[WOS]	Engineering ; Mathematics
关键词[WOS]	WAVELET SHRINKAGE ; NOISE ESTIMATION ; DOMAIN ; DISTRIBUTIONS
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000398481000001
内容类型	期刊论文
源URL	[http://ir.sia.cn/handle/173321/20295]
专题	沈阳自动化研究所_工业控制网络与系统研究室
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.