| 改进小波阈值法在变形监测数据处理中的应用 |
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| 引用本文： | 王旭.改进小波阈值法在变形监测数据处理中的应用[J].测绘与空间地理信息,2018(1):83-85. |
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| 作者姓名： | 王旭 |
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| 作者单位： | 辽宁林业职业技术学院,辽宁 沈阳,110101 |
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| 基金项目： | 2015年辽宁林业职业技术学院院级自然科学课题——小波阈值去噪法在变形监测数据处理中的应用研究 |
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| 摘 要： | 阈值的选取和小波函数的构造是小波阈值去噪的关键,本文从两个方面分别进行阐述。首先,通过对传统小波阈值去噪方法的分析,提出了确定阈值的新方法;其次,构造出新的小波阈值函数去处理小波系数。然后,通过对一组离散变形监测数据进行去噪处理,验证了改进小波阈值法的优越性和有效性。
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| 关 键 词： | 变形监测 小波去噪 阈值函数 阈值 均方误差 deformation monitoring wavelet denoise thresholds function thresholds MSE |
Application of Improved De-noising Algorithm of Wavelet Threshold to Deformation Monitoring Data |
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| WANG Xu.Application of Improved De-noising Algorithm of Wavelet Threshold to Deformation Monitoring Data[J].Geomatics & Spatial Information Technology,2018(1):83-85. |
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| Authors: | WANG Xu |
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| Abstract: | The key of wavelet thresholding denoise is constructing thresholding function and selecting thresholding. This paper improves from two sides respectively. First, A new method of threshold determination is proposed by the analysis of the traditional wavelet threshold denoising method, Second, constructing a new wavelet threshold function to deal with the wavelet coefficients. At last, this article will process a set of discrete deformation monitoring data relating to the improved method. The result shows that the superiority and effectiveness of the improved wavelet threshold method. |
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