首页> 外文会议>2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)论文集 >A NEW SIGNAL DE-NOISING ALGORITHM COMBINING IMPROVED THRESHOLDING AND PATTERNSEARCH ALGORITHM
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A NEW SIGNAL DE-NOISING ALGORITHM COMBINING IMPROVED THRESHOLDING AND PATTERNSEARCH ALGORITHM

机译:改进的阈值和模式搜索算法相结合的新信号去噪算法

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A new de-noising algorithm combining improved thresholding and patternsearch (PS) algorithm was put forward. The improved thresholding method based on Donoho's method. The traditional wavelet thresholding method includes two kinds: hard-thresholding and soft-thresholding. The hard-thresholding methods may lead to oscillation of the reconstructed signal, and the soft-thresholding methods may cause constant deviations between the estimated wavelet and original wavelet coefficients. The improved threshhoding method can overcome these defects, which was better in keeping trade-off between smoothness and remaining edge of the original signal. A coefficient β which is flexible was set up in the improvedthresholding method, how to find the appropriate β isimportant for the improved thresholding de-noising, furthermore, the improved thresholding methods were combined with some parameters such as wavelet function, decomposition scales etc., the effectiveness of signal de-noising is quite different. Now, most of researchers are usually selected semi-empirically or empirically these parameters, which cannot ensure that the de-noising performance is optimal in some sense. In order to solve these problems, the pattersearch function of Matlab can be adopted to guide the selection of these parameters. The effectiveness of the new method is validated by the results of the simulated experiment.
机译:提出了一种新的结合改进的阈值和模式搜索(PS)算法的降噪算法。基于Donoho方法的改进阈值方法。传统的小波阈值化方法包括硬阈值法和软阈值法两种。硬阈值方法可能导致重构信号的振荡,而软阈值方法可能导致估计的小波系数与原始小波系数之间存在恒定偏差。改进的脱阈方法可以克服这些缺陷,更好地保持了平滑度和原始信号的剩余边缘之间的折衷。在改进的阈值方法中建立了一个灵活的系数β,如何找到合适的β对于改进的阈值去噪很重要,此外,改进的阈值方法还结合了小波函数,分解尺度等参数,信号去噪的有效性是完全不同的。现在,大多数研究人员通常都是半经验地或经验地选择这些参数,这不能确保消噪性能在某种意义上是最佳的。为了解决这些问题,可以采用Matlab的模式搜索功能来指导这些参数的选择。仿真实验结果验证了该方法的有效性。

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