| 基于支持向量机的数字调制信号识别 |
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| 引用本文： | 李艳玲,李兵兵,刘明骞,尹昌义. 基于支持向量机的数字调制信号识别[J]. 计算机与现代化, 2011, 0(3): 1-4. DOI: 10.3969/j.issn.1006-2475.2011.03.001 |
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| 作者姓名： | 李艳玲 李兵兵 刘明骞 尹昌义 |
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| 作者单位： | 1. 河南农业大学信息与管理科学学院,河南,郑州,450002;西安电子科技大学ISN国家重点实验室,陕西,西安,710071
2. 西安电子科技大学ISN国家重点实验室,陕西,西安,710071 |
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| 基金项目： | 国家自然科学基金资助项目，国家863计划项目，高等学校学科创新引智计划项目 |
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| 摘 要： | 针对神经网络分类器容易陷入局部最小值和不适用于小样本的缺点,提出一种应用零中心瞬时特征提取法提取分类特征,采用支持向量机分类器进行数字调制信号识别的方法。与传统的神经网络方法相比,该方法具有更好的泛化推广能力。实验仿真结果表明,该调制识别方法在小样本下具有较高的识别率。
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| 关 键 词： | 调制识别 支持向量机 特征提取 |
Digital Modulation Signal Recognition Based on SVM |
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| LI Yan-ling,LI Bing-bing,LIU Ming-qian,YIN Chang-yi. Digital Modulation Signal Recognition Based on SVM[J]. Computer and Modernization, 2011, 0(3): 1-4. DOI: 10.3969/j.issn.1006-2475.2011.03.001 |
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| Authors: | LI Yan-ling LI Bing-bing LIU Ming-qian YIN Chang-yi |
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| Affiliation: | 1.College of Information and Management Science,Henan Agricultural University,Zhengzhou 450002,China; 2.National Key Laboratory of ISN,Xidian University,Xi＇an 710071,China) |
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| Abstract: | Aiming at the two shortcomings of easy to fall into local minimum and inappropriate for small sample of neural network classifier,a new method of modulation recognition for digital signals is proposed using zero-center instantaneous features extraction to extract characteristics and based on support vector machine（SVM）.Compared with traditional algorithms based on neural networks,this algorithm has better generalization ability.Computer simulation results indicate that the method has the high recognition rate with less samples. |
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| Keywords: | modulation recognition support vector machine feature extraction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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