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| 基于SVM的多类模拟调制方式识别算法 | |
| 引用本文： | 孙建成,张太镒,刘海员. 基于SVM的多类模拟调制方式识别算法[J]. 电子科技大学学报(社会科学版), 2006, 0(2) |
| 作者姓名： | 孙建成 张太镒 刘海员 |
| 作者单位： | 江西财经大学电子学院 南昌330013(孙建成)，西安交通大学电子与信息工程学院 西安710049(张太镒，刘海员) |
| 基金项目： | 国家自然科学基金资助项目(90207012) |
| 摘 要： | 提出了一种基于支持向量机的多类模拟调制方式识别算法。该算法通过分析模拟调制信号的特点,提取有效的特征向量以区分不同的调制方式,并基于支持向量机和判决树分类思想,将特征向量映射到高维空间中加以分类。仿真结果表明:在具有加性带限高斯噪声的环境下,信噪比不小于10dB时,识别正确率大于90%。 |
| 关 键 词： | 支持向量机 调制方式识别 特征提取 |
Multi-Class Analogue Modulation Recognition Algorithms Based on Support Vector Machines |
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| SUN Jian-cheng,ZHANG Tai-yi,LIU Hai-yuan. Multi-Class Analogue Modulation Recognition Algorithms Based on Support Vector Machines[J]. Journal of University of Electronic Science and Technology of China(Social Sciences Edition), 2006, 0(2) | |
| Authors: | SUN Jian-cheng ZHANG Tai-yi LIU Hai-yuan |
| Affiliation: | SUN Jian-cheng1,ZHANG Tai-yi2,LIU Hai-yuan2 |
| Abstract: | An algorithm based on Support Vector Machines(SVM) for recognition of analogue modulation signals is presented. By analyzing the modulation signals, a set of key features for identifying different types of analogue modulation are extracted and are mapped into the high dimension space. The classification is carried out in the high dimension space based on SVM and decision tree. The result shows that all types of analogue modulation can be classified with success rate more than 90% when SNR higher than10 dB. |
| Keywords: | support vector machines modulation recognition feature extraction |
| 本文献已被 CNKI 等数据库收录！ | |