A NEW SIGNAL DE-NOISING ALGORITHM COMBINING IMPROVED THRESHOLDING AND PATTERNSEARCH ALGORITHM
A new de-noising algorithm combining improved thresholding and patternsearch (PS) algorithm was put forward. The improved thresholding method based on Donohos 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.
Signal de-noising Improved thresholding Patternsearch Hard-thresholding Soft-thresholding
XIAOJING CHEN DI WU YONG HE SHOU LIU
College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China Depa College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310029, China Department of Physics, Xiamen University, Xiamen, 361005 China
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
2729-2733
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）