计算机科学 ›› 2011, Vol. 38 ›› Issue (5): 64-66.
• 计算机网络与信息安全 • 上一篇 下一篇
刘明骞,李兵兵,刘涵
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基金资助:
LIU Ming-qian,LI Bing-bing,LIU Han
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摘要: 针对正确率不能客观全面地评估字调制信号识别性能的问题,提出采用受试者操作特征(ROC)曲线下的面积(AUC)对最小二乘支持向量机分类器和传统的神经网络分类器进行性能评佑。首先提取J个特征参数,然后分别采用最小二乘支持向量机分类器和神经网络分类器成功地实现了数字调制信号识别,最后通过计算ROC曲线下的AUC值来评估分类器的优劣。仿真实验结果表明,最小二乘支持向量机分类器比神经网络分类器的平均性能好。
关键词: 性能评估,AUC,ROC曲线,支持向量机,调制识别
Abstract: Because the accurate rate could not be evaluated objectively and overall in recognition of digital modulation,it was proposed that area under receiver operating characteristic(AUC) was used for assessing the LS-SVM classifier and NN classifier's performance. After using the five characteristics parameters, the classification of digital modulation was successfully realized by adopting the LS-SVM classifier and NN classifier. The values of AUC were used for evaluating the merits and demerits of classifiers. The relevant simulation results shown the average performance of the LS-SVM classifier is better than that of the NN classifier.
Key words: Performance evaluation, AUC, ROC curve, SVM, Modulation recognition
刘明骞,李兵兵,刘涵. 数字调制信号识别性能的评估方法[J]. 计算机科学, 2011, 38(5): 64-66. https://doi.org/
LIU Ming-qian,LI Bing-bing,LIU Han. Performance Evaluation Algorithm of Digital Modulation Signals Recognition[J]. Computer Science, 2011, 38(5): 64-66. https://doi.org/
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