Supervised and Unsupervised Subband Adaptive Denoising Frameworks with Polynomial Threshold Function
文献类型：期刊论文
| 作者 | Gong TR(宫铁瑞) ; Yang ZJ(杨志家); Wang GS(王庚善); Jiao P(焦平)
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| 刊名 | Mathematical Problems in Engineering
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| 出版日期 | 2017 |
| 卷号 | 2017页码:1-12 |
| ISSN号 | 1024-123X |
| 产权排序 | 1 |
| 通讯作者 | 宫铁瑞 |
| 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 |
| 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. |
入库方式： OAI收割
来源：沈阳自动化研究所
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