| 基于离散小波变换的近程信号自动识别 |
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| 引用本文： | 谢鑫,李国林,路翠华.基于离散小波变换的近程信号自动识别[J].海军航空工程学院学报,2004,19(2):229-232. |
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| 作者姓名： | 谢鑫 李国林 路翠华 |
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| 作者单位： | 1. 海军航空工程学院研究生管理大队
2. 海军航空工程学院军械工程系,烟台,264001 |
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| 摘 要： | 进行信号识别的关键在于利用有限信号数据提取出有效的信号特征,然后根据这些特征作出判决。文中阐述了利用离散小波变换对近程信号进行分解处理,并结合具体应用背景,提取小波分解的细节作为信号识别的特征参量。仿真实验表明,基于小波分解的特征提取过程对噪声有较好的抑制能力,小波变换的应用能够有效提高对近程信号识别的能力。
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| 关 键 词： | 信号识别 特征提取 小波变换 |
| 修稿时间： | 2003年11月15 |
Recognition of Proximity Radio Signals Based on the Discrete Wavelet Transformation |
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| XIE Xin,LI Guo-lin,LU Cui-hua.Recognition of Proximity Radio Signals Based on the Discrete Wavelet Transformation[J].Journal of Naval Aeronautical Engineering Institute,2004,19(2):229-232. |
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| Authors: | XIE Xin LI Guo-lin LU Cui-hua |
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| Institution: | XIE Xin LU Cui-hua Graduate Students'Brigade of NAEI,LI Guo-hn Department of Automatic Control Engineering,NAEI,Yantai,264001 |
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| Abstract: | The kernel of signal recognition is how to extract active features of signals from finite signal data and make a decision.In this paper,the proximity signals were decomposed using DWT,and according to the material applications,the details of DWT decomposition were extracted for signal recognition.After some emulation experiments,a conclusion was drawn that DWT had a good representation in signal recognition. |
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| Keywords: | signal recognition feature extraction wavelet transformation |
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