| 冲击噪声背景下基于KPCA和C-SVM的频谱检测算法 |
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| 引用本文： | 赵季红,张艳平,曲桦,徐西光.冲击噪声背景下基于KPCA和C-SVM的频谱检测算法[J].电视技术,2017,41(2):65-69. |
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| 作者姓名： | 赵季红 张艳平 曲桦 徐西光 |
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| 作者单位： | 1. 西安邮电大学通信与信息工程学院,陕西西安710061;西安交通大学电子与信息工程学院,陕西西安710049;2. 西安邮电大学通信与信息工程学院,陕西西安,710061;3. 西安交通大学电子与信息工程学院,陕西西安,710049 |
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| 基金项目： | ]：国家863计划项目(No.2014AA01A706)；国家自然科学(No.61372092) |
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| 摘 要： | 针对背景噪声是冲击噪声,且在低信噪比中,二级用户检测性能低的问题,提出了核主成分分析(Kernel PrincipalComponent Analysis,KPCA)和C-支持向量机(Support Vector Machine,SVM)的频谱检测方法.提取接收信号的循环谱特征,核主成分分析对信号特征进行降维,提取出信号的主要非线性特征,再结合C-SVM对接收信号进行分类.仿真结果表明,在冲击噪声背景下,低信噪比中,与PCA-SVM、SVM算法进行比较,所提算法能够提高次级用户的检测性能.
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| 关 键 词： | 冲击噪声 循环谱特征 核主成分分析 C-支持向量机 |
| 收稿时间： | 2016/6/22 0:00:00 |
| 修稿时间： | 2016/7/17 0:00:00 |
Spectrum Detection algorithm Based on KPCA and C-SVM in The Background of Impulse Noise |
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| ZHAO Jihong,ZHANG Yanping,QU Hua and XU Xiguang.Spectrum Detection algorithm Based on KPCA and C-SVM in The Background of Impulse Noise[J].Tv Engineering,2017,41(2):65-69. |
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| Authors: | ZHAO Jihong ZHANG Yanping QU Hua and XU Xiguang |
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| Abstract: | In order to address the low accuracy in the case of impulse noise and low SNR , a spectrum detection method based on kernel principal component analysis and support vector machine is proposed. The cyclic spectrum characteristic of the received signal is extracted . Kernel principal component analysis reduces the dimension of the signal feature and extracts the main feature of the signal. Then the support vector machine is applied to classify the received signals. The simulation results show that the proposed method can improve the detection performance of the secondary users in the impulse noise environment and low SNR compared with PCA-SVM and SVM. |
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| Keywords: | impulsive noise cyclic spectrum characteristic kernel principal component analysis C-support vector machine |
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