| 小波阈值降噪算法中最优分解层数的自适应选择 |
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| 引用本文： | 蔡铁, 朱杰.小波阈值降噪算法中最优分解层数的自适应选择[J].控制与决策,2006,21(2):217-0220. |
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| 作者姓名： | 蔡铁 朱杰 |
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| 作者单位： | 上海交通大学,电子工程系,上海,200030 |
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| 摘 要： | 小波阚值降噪算法是一种去除数字信号中白噪声的有效算法．针对加性高斯白噪声的情况，提出一种自适应小波降噪算法，用于语音信号的增强．它能根据带噪信号的特点，自适应选择小波变换的最优分解层数．实验结果表明，该算法比经典的小波降噪算法具有更好的降噪效果，能有效提高算法的实用性能．
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| 关 键 词： | 语音增强 小波降噪 分解层数 奇异谱分析 |
| 文章编号： | 1001-0920（2006）02-0217-04 |
| 收稿时间： | 2005-01-04 |
| 修稿时间： | 2005-03-28 |
Adaptive Selection of Optimal Decomposition Level in Threshold De-noising Algorithm Based on Wavelet |
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| CAI Tie,ZHU Jie.Adaptive Selection of Optimal Decomposition Level in Threshold De-noising Algorithm Based on Wavelet[J].Control and Decision,2006,21(2):217-0220. |
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| Authors: | CAI Tie ZHU Jie |
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| Affiliation: | Department of Electronic Engineering, Shanghai Jiaotong University , Shanghai 200030, China |
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| Abstract: | Threshold de-noising in wavelet domain is an efficient algorithm to reduce the white noise in digital signal, In the presence of additive white Gaussian noise, an adaptive wavelet-based de-noising algorithm for speech enhancement applications is proposed. It can adaptively select the optimal decomposition level of wavelet transformation according to the characteristics of noisy speech. The experimental results demonstrate that this proposed algorithm outperforms the classical wavelet thresholding method and effectively improves the practicability. |
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| Keywords: | Speech enhancement Wavelet de-noising Decomposition level Singular spectrum analysis |
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