| 一种新的自适应数字滤波方法的研究 |
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| 引用本文： | 武优西,李建满,米少华,侯丹丹. 一种新的自适应数字滤波方法的研究[J]. 计算机工程与应用, 2012, 48(2): 145-147 |
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| 作者姓名： | 武优西 李建满 米少华 侯丹丹 |
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| 作者单位： | 河北工业大学 计算机与软件学院，天津 300401 |
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| 基金项目： | 河北省教育厅科研计划项目（No.2007430） |
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| 摘 要： | 自适应数字滤波中理想信号通常难于确定。针对这一问题，根据均方误差和高频信号的特征，将二者结合起来考虑，提出一种新的自适应数字滤波的方法。应用该方法在252组真实实验数据中进行相应的自适应滤波测试，并对滤波结果分别采用BP神经网络和支持向量机两种分类方法进行分类测试。实验结果表明，新方法具备良好的滤波效果。
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| 关 键 词： | 自适应滤波 均方误差 高频 折中评价 |
| 修稿时间： | |
Research on self-adapting digital filter |
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| WU Youxi , LI Jianman , MI Shaohua , HOU Dandan. Research on self-adapting digital filter[J]. Computer Engineering and Applications, 2012, 48(2): 145-147 |
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| Authors: | WU Youxi LI Jianman MI Shaohua HOU Dandan |
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| Affiliation: | School of Computer Science and Software, Hebei University of Technology, Tianjin 300401, China |
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| Abstract: | It is difficult to identify the ideal signals in the self-adapting digital filter.In order to solve this problem,taking account of the mean squared error and the characters of high-frequency signal,this paper puts forward a new self-adapting digital filter.252 real data are used to test the effects of the self-adapting filter.In order to evaluate the filter effects,Back-Propagation（BP）neural network and Support Vector Machine（SVM）are respectively employed to classify the results of the data sets.The experimental results show that this method has the best performance among all filtering methods. |
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| Keywords: | self-adapting filter mean squared error high frequency compromise evaluation |
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